# Foundations of Computational Interaction — FULL RESEARCH CORPUS Abbreviation: fci Version: v0.5.0 | Generated: unspecified | Files: 150 | Lines: 42,100 | Payload: 2228.4 KiB Source path: /Users/zachshallbetter/Projects/_protocols/foundations-of-computational-interaction Bundle name: llm-full-docs-fci Corpus Payload SHA-256: 339205c034f58a52b92d9218ac4b81db6c5cf244444be9901b82248bd6db32fd TABLE OF CONTENTS: - .agents/AGENTS.md (166 lines, 14.7 KiB) - AGENTS.md (14 lines, 0.9 KiB) - CLAUDE.md (153 lines, 7.8 KiB) - LICENSE (12 lines, 0.6 KiB) - LICENSES.md (28 lines, 2.0 KiB) - README.md (151 lines, 7.5 KiB) - app/AUTHORITY.md (47 lines, 1.8 KiB) - app/CONCEPT_VALIDATION.md (172 lines, 16.3 KiB) - app/CONFORMANCE.md (61 lines, 2.5 KiB) - app/DOCUMENT_MAP.md (35 lines, 4.0 KiB) - app/Makefile (141 lines, 6.5 KiB) - app/NAMING.md (34 lines, 1.4 KiB) - app/README.md (132 lines, 7.8 KiB) - app/RELEASE_NOTES.md (61 lines, 3.5 KiB) - app/VERSIONING.md (40 lines, 2.5 KiB) - app/examples/PAPER_ALIGNMENT.md (32 lines, 4.3 KiB) - app/examples/README.md (287 lines, 13.6 KiB) - app/examples/benchmarks/README.md (18 lines, 1.0 KiB) - app/examples/benchmarks/overclaim-benchmark.c (74 lines, 2.9 KiB) - app/examples/benchmarks/projection-benchmark.c (72 lines, 2.8 KiB) - app/examples/conformance.c (30 lines, 0.8 KiB) - app/examples/door.c (59 lines, 2.0 KiB) - app/examples/manifest.csv (9 lines, 1.6 KiB) - app/examples/studies/CIS-EX-008/contracts/README.md (28 lines, 1.4 KiB) - app/examples/studies/CIS-EX-008/contracts/behavioral-evidence.json (55 lines, 4.0 KiB) - app/examples/studies/CIS-EX-008/contracts/interaction.json (65 lines, 4.4 KiB) - app/examples/studies/CIS-EX-008/contracts/measurement-belief.json (49 lines, 3.3 KiB) - app/examples/studies/CIS-EX-008/contracts/measurement-completion.json (49 lines, 3.1 KiB) - app/examples/studies/CIS-EX-008/contracts/measurement-discovery.json (49 lines, 3.2 KiB) - app/examples/studies/CIS-EX-008/contracts/measurement-invalid-attempt.json (49 lines, 3.2 KiB) - app/examples/studies/CIS-EX-008/contracts/measurement-recovery.json (49 lines, 3.2 KiB) - 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docs/01_Knowledge_System_of_Record/05_Specifications/Contracts/Contract_ID_Registry.md (34 lines, 2.3 KiB) - docs/01_Knowledge_System_of_Record/06_Graph/PAPER_DEPENDENCY_EDGES.csv (16 lines, 2.3 KiB) - docs/01_Knowledge_System_of_Record/06_Graph/PAPER_DEPENDENCY_NODES.csv (17 lines, 2.0 KiB) - docs/01_Knowledge_System_of_Record/07_Reviews/Computational_Interaction_Science_Wikipedia_Readiness_Review_v0.2.md (33 lines, 2.8 KiB) - docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Glossary.md (2154 lines, 81.2 KiB) - docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Ontology.md (789 lines, 23.1 KiB) - docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Graphs/Knowledge_Graph_Edges.csv (43 lines, 2.9 KiB) - docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Graphs/Knowledge_Graph_Nodes.csv (110 lines, 18.8 KiB) - docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Artifact_Index.csv (68 lines, 13.6 KiB) - docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Artifact_Index.md (154 lines, 22.5 KiB) - 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docs/01_Knowledge_System_of_Record/10_Governance/Participant_Data_Management_Plan.md (51 lines, 2.5 KiB) - docs/01_Knowledge_System_of_Record/10_Governance/README.md (39 lines, 2.1 KiB) - docs/01_Knowledge_System_of_Record/10_Governance/consent-record.schema.json (38 lines, 1.5 KiB) - docs/01_Knowledge_System_of_Record/10_Governance/data-management-plan.schema.json (126 lines, 4.9 KiB) - docs/01_Knowledge_System_of_Record/10_Governance/ethics-gate-assessment.schema.json (113 lines, 4.5 KiB) - docs/01_Knowledge_System_of_Record/README.md (15 lines, 0.6 KiB) - docs/02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.md (2397 lines, 109.6 KiB) - docs/02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.md (1134 lines, 62.4 KiB) - docs/02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.md (979 lines, 64.2 KiB) - docs/02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.md (1058 lines, 54.0 KiB) - 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docs/90_Project/Audits/Editorial_Normalization_v1.1.1/SHA256SUMS.txt (92 lines, 9.8 KiB) - docs/90_Project/Audits/Editorial_Normalization_v1.1.1/Source_Data/Authoritative_Metadata_Sources.md (8 lines, 0.6 KiB) - docs/90_Project/Audits/Editorial_Normalization_v1.1.1/Source_Data/build_summary.json (15 lines, 0.5 KiB) - docs/90_Project/Decisions/Consolidated_RC/FILE_INVENTORY.txt (179 lines, 14.2 KiB) - docs/90_Project/Decisions/Consolidated_RC/OVERLAP_AND_SUPERSESSION.md (16 lines, 1.3 KiB) - docs/90_Project/Decisions/Consolidated_RC/SHA256SUMS.txt (179 lines, 26.1 KiB) - docs/90_Project/Decisions/Consolidated_RC/SOURCE_PACKAGES.txt (10 lines, 0.5 KiB) - docs/90_Project/Manifests/FILE_MANIFEST.csv (283 lines, 42.4 KiB) - docs/90_Project/Manifests/MIGRATION_MAP.md (15 lines, 1.1 KiB) - docs/90_Project/Manifests/SHA256SUMS.txt (282 lines, 38.1 KiB) - docs/90_Project/Negative_Results.md (79 lines, 4.5 KiB) - docs/90_Project/Release_Notes_v1.0.md (46 lines, 4.2 KiB) - docs/90_Project/Repositioning_Analysis_v1.0.md (100 lines, 6.5 KiB) - docs/90_Project/Research_Practices.md (149 lines, 7.0 KiB) - docs/90_Project/Reviews/Comprehensive_Repository_Review_v1.0.md (369 lines, 19.1 KiB) - docs/90_Project/Reviews/Program_TODO_v1.0_Closeout.md (414 lines, 22.6 KiB) - docs/90_Project/Version_2/Validation_Matrix.csv (10 lines, 1.4 KiB) - docs/90_Project/Version_2/Version_2_Research_Program.md (57 lines, 4.3 KiB) - docs/CHANGELOG.md (71 lines, 10.5 KiB) - docs/README.md (20 lines, 1.2 KiB) - docs/ROADMAP.md (5 lines, 0.3 KiB) - docs/START_HERE.md (18 lines, 1.3 KiB) - docs/VERSION (1 lines, 0.0 KiB) - scripts/check-doc-links.py (92 lines, 3.4 KiB) - scripts/check-structure.py (66 lines, 2.2 KiB) - scripts/gen-llms.py (189 lines, 7.8 KiB) ======================================================================== ======================================================================== ## FILE: .agents/AGENTS.md (166 lines, 14.7 KiB) ======================================================================== # Workspace Agent Rules: Foundations of Computational Interaction These rules guide the research, editorial refactoring, repositioning, and software development within the Foundations of Computational Interaction repository. --- ## 1. Guiding Principle Do not ask whether the work succeeds in defining a new discipline. Instead, evaluate whether it succeeds in constructing a coherent, scientifically useful conceptual model of computational interaction. All editorial decisions must reinforce that objective. --- ## 2. Architectural Layers The repository corpus must be framed around three distinct layers: 1. **Layer 1 — The Scholarly Program:** The long-term research effort, referred to as **Foundations of Computational Interaction**. This is the epistemic infrastructure for the scientific study of computational interaction. It specifies the conditions under which computational interaction can be represented, observed, measured, and compared. It includes historical research, ontology, semantics, representation, projection, interpretation, observation, evidence, measurement, and comparison. It is not itself a model. 2. **Layer 2 — The Principal Scientific Contribution:** A formal, conceptual model of computational interaction. It is described generically as "a formal model of computational interaction" or "a foundational model of computational interaction." It defines entities, relationships, representations, transformations, observations, evidence, measurement, and comparison. It is *not* a scientific discipline, and does *not* replace HCI or Computational Interaction. 3. **Layer 3 — Scientific Models (Downstream Consumers):** Explanation and prediction are not produced by the foundational model itself. They are produced by scientific models (e.g., cognitive, ecological, probabilistic, activity-theoretic, or economic models) built within the framework established by the foundational work. The foundational model supports them rather than replaces them. --- ## 3. The Epistemological Questions Every component of the program answers a necessary epistemological question to establish the conditions under which explanation and prediction become scientifically meaningful: * **Ontology:** *What exists?* * **Semantics:** *What do operations mean?* * **Representation:** *How is it represented?* * **Projection:** *What survives transformation?* * **Interpretation:** *What is system action vs. user purpose?* * **Opportunity:** *What is the fundamental unit of choice?* * **Observation:** *What can be observed?* * **Evidence:** *What counts as evidence?* * **Measurement:** *What can be measured?* * **Comparison:** *What can be compared?* --- ## 4. Editorial Guidelines * **Scientific Language:** Replace institutional language with scientific language. Avoid phrasing like *"Computational Interaction Science proposes/defines..."* or *"the discipline of Computational Interaction Science."* Prefer *"FCI...",* *"the model defines...",* *"this work develops...",* *"this research establishes...",* or *"this paper defines..."* * **Branding Reduction:** Minimize proper noun branding and acronyms. Prefer natural scientific prose (e.g., *"The model distinguishes...",* *"The model represents..."*). * **Relationship to Existing Work:** Frame the relationship as complementary: * *Existing Computational Interaction:* Develops computational methods for understanding and optimizing interaction. * *This Body of Work:* Develops a formal conceptual model for representing, observing, measuring, and comparing computational interaction. * **Introductions:** Every paper's introduction must state its specific role in the overall model (e.g., *"This paper defines the ontological foundation of FCI"*). --- ## 5. Research Program & Scientific Boundaries (Phase 0) ### 5.1 Mission & Central Question * **Mission:** Decide whether interaction merits a distinct computational science. Do not defend a thesis blindly, write papers first, design products, or invent unnecessary branding terms. Success is defined as a truthful recommendation to: `proceed`, `revise`, `merge`, or `abandon`. * **Central Question:** Can interaction be a coherent scientific unit independent of interfaces, products, and implementations? * **Implementation Independence:** This is required. If the experimental platform (Observatory) and simulation kernel (Fundamental) disappear, the conceptual theory must still remain valid. Software is the apparatus/reference implementation, not the contribution. ### 5.2 Observations & Lived Experience * **Core Observation:** People with different lived, cultural, linguistic, professional, technical, or material histories may perceive and use the same software differently. * **Exposure-Based Origins:** Recurring differences observed in community engagements (e.g., orientation, navigation, collaboration, verification) must not be assumed to have essentialist cultural causes. Investigate specific mechanisms, exposure histories, and interaction ecologies. * **The Work Thesis:** Interaction behavior emerges from accumulated lifetime exposure to tools, software, games, education, language, writing systems, community practice, governance, workflows, physical environment, visual traditions, material culture, and institutions. ### 5.3 Candidate Field Definition & Negative Space * **Computational Interaction Science (Proposed):** The study of how people perceive, interpret, act on, adapt to, and transfer across structured information systems, and how these processes can be formally described, measured, and modeled. * **Negative Space:** This work is *not* UX design, usability, design systems, personality models, learning styles, cultural taxonomy, demographic segmentation, marketing, AI interface models, telemetry platforms, or accessibility standards. If the model collapses into existing fields without material loss, merge or stop. * **Research Stance:** Adversarial and constructive. Assume current terms are invalid. Challenge novelty, need, scope, falsifiability, operationalization, ethics, and overlap. ### 5.4 Adjacent Fields & Existing Models * **Adjacent Fields to Analyze:** HCI, Human Factors, Cognitive Science, Cog Psychology, Ecological Psychology, Distributed Cognition, Situated Cognition, Activity Theory, Embodied Cognition, Information Foraging, Info Visualization, Semiotics, Anthropology, Cross-Cultural HCI, Learning Science, Behavioral Economics, Systems Theory, Cybernetics, Complexity, Human-AI, Game Studies. * **Existing Models to Evaluate:** Affordances, Seven Stages of Action, GOMS/KLM, Mental Models, Distributed Cog, Activity Theory, Situated Action, Embodied Cog, Info Foraging, Cognitive Load, Flow, Technology Acceptance Model (TAM), Adaptive Interfaces, Cross-Cultural HCI. * *For each field/model:* Analyze scope, unit of analysis, mechanisms, empirical strength, limits, and overlaps to identify genuine gaps. ### 5.5 Core Concepts & Priority Topics 1. **Interaction Ecology:** Lifetime habitats and accumulated experiences shape approaches to unfamiliar systems. Exposure profiles predict behavioral similarity better than demographics. 2. **Interaction Morphology:** Visual and spatial composition (shape, color, density, alignment, symmetry, positioning) encodes preconscious structural expectations before semantic interpretation. 3. **Interaction Grammar:** Interfaces express action grammars transferring across systems beyond low-level input events. 4. **Behavioral Opportunities:** The fundamental unit of choice/measurement. Defined as: `Known State + Visible Information + Available Actions + Choice/Avoidance + Outcome`. Relative models predict behavior better than event counts or self-reports. 5. **Semantic Representation & Transfer:** Translation loss across representations during form changes tracks semantic fidelity and prior grammar exposure, not surface similarity. ### 5.6 Context Variables * Analyze context variables strictly as moderators, covariates, exposures, or confounds—never as essentialist identities. * **Variables include:** Age band, current/raised region, migration, languages/scripts, reading direction, education/occupation, community roles, device/software history, gaming, visual/material traditions, collaborative norms, institutional exposure, and access needs. --- ## 6. Repository Rules & Infrastructure > **Operational conventions** — the verification gate, CI, per-layer versioning and changelogs, branch > and commit conventions — are in [CLAUDE.md](../CLAUDE.md). Claim-strength practices (preregistration, > the discovery criterion, negative results, evidence provenance) are in > [docs/90_Project/Research_Practices.md](../docs/90_Project/Research_Practices.md). ### 6.1 Authority and Scope Apply the authority order in [app/AUTHORITY.md](../app/AUTHORITY.md) (final synthesis determination, then canonical glossary, then relational ontology, …). Treat [docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Ontology.md](../docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Ontology.md) as the current label and determination freeze, contract schemas as draft 0.x normative candidates, C as a deterministic subset, and examples as explanatory derivatives. Never let code, bibliography records, or generated files silently change theory. Use **FCI** as the preferred short name and **Interaction Participant** as the general participant category. Retain the `cis_` C namespace only under the legacy policy in [NAMING.md](../app/NAMING.md). Use `formal trace`, `execution record`, or `instrument record` unless an empirical Behavioral Evidence Contract is applied. ### 6.2 Examples and Visual Review Rules Every executable, interactive model, visualization, or worked scenario added to this repository must be an identified example. 1. Allocate the next unused `CIS-EX-NNN` identifier in `examples/manifest.csv`. 2. Put the identifier and applicable theory version in the source artifact. 3. Add a complete `examples/README.md` definition covering purpose, inputs or controls, concepts exercised, expected behavior, non-claims, and validation. 4. Keep editable visualization fragments under `examples/visualizations/src/` and generated standalone files under `examples/visualizations/`. 5. Add golden assertions or behavioral tests wherever the example makes an executable claim. 6. Align every interactive figure in [examples/PAPER_ALIGNMENT.md](../app/examples/PAPER_ALIGNMENT.md), including canonical concepts, internal research basis, candidate source keys, and claim boundary. 7. Run `make test`; missing identities, missing definitions, and stale generated visualization output are failures. **Visual Quality Review Rules:** Interactive figures must pass visual review at both wide and narrow widths: * The primary relationship must be visually dominant. * Controls and evidence must be hierarchically distinct. * Color must have a stable, semantic role. * Empty states must remain compact. * Text must not clip or overflow. * Focusable controls must use native keyboard behavior. * No decorative treatment should imply a stronger research claim than is supported. Never reuse or renumber an example identifier. A material semantic change gets a new identifier; a correction that restores the documented contract retains the existing identifier and updates its validation record. --- ## 7. Quality Gates & Publication Rules * **Canonical Canon:** One primary contribution per paper. Theory before implementation, definitions before use, assumptions explicit, observations separate from inference, claims falsifiable. * **Quality Gate Checks:** * Every claim must be cited or explicitly labeled as an inference. * Every new term must be systematically compared to existing literature vocabulary. * Every gap must be evidenced, and every hypothesis must be operationalizable. * Every identity claim must be non-essentialist. * Every recommendation must include its failure conditions. --- ## 8. Agent Execution Methodology & Forward-Thinking Completion Engine To ensure all research, coding, documentation, and refactoring tasks are executed with maximum intelligence and completed to end-to-end working state, agents must strictly follow these 5 core execution rules: ### 8.1 Ambient Adaptation & Engineering Judgment * **Style & Convention Matching**: Read surrounding files before editing. Match comment density, naming conventions, architectural idioms, and structural patterns. * **Root-Cause Resolution**: Inspect actual log/test outputs and trace upstream data flow. Address underlying logic errors rather than applying superficial symptom patches or suppressing errors. ### 8.2 Autonomous Execution to Completion * **End-to-End Ownership**: Do not halt halfway or stop at draft code/plans. Drive tasks through research, implementation, build validation, and verification until the requested outcome is fully realized. * **Self-Correction & Autonomous Momentum**: If a chosen path hits a blocker, evaluate alternative approaches immediately. Log the deviation in `scratch/implementation-notes.md` and proceed with the best alternative rather than halting execution to ask trivial questions. ### 8.3 Unknowns Discovery Framework (Blind Spot Pass & Pre/During/Post Workflow) Map tasks across the 4 Context Quadrants before and during execution: 1. **Known Knowns**: Explicit user requirements in the prompt. 2. **Known Unknowns**: Identified gaps requiring investigation before coding. 3. **Unknown Knowns**: Implicit expectations and visual taste ("know it when I see it"). 4. **Unknown Unknowns**: Unconsidered architectural traps, edge cases, or domain blind spots. * **Pre-Implementation Blind Spot Pass**: Scan the codebase for hidden dependencies and domain risks before proposing solutions. * **Isolated Mocks & Prototypes**: Create lightweight mocks for UX/visual tasks with high "Unknown Knowns" to validate user preferences before modifying production state. * **Decision-Focused Planning**: Structure implementation plans around critical decisions (data models, interfaces, user-facing behavior) rather than routine boilerplates. ### 8.4 Live Implementation Ledger (`scratch/implementation-notes.md`) For non-trivial tasks, maintain a scratch ledger at `/brain//scratch/implementation-notes.md` recording: * **Decisions & Rationale**: Key architectural choices and why alternative paths were bypassed. * **Deviations**: Edge cases encountered that required adapting the initial plan. * **Verification Proof**: Command outputs, test results, and runtime build metrics confirming correctness. ### 8.5 Empirical Runtime Verification * **No Premature Success Claims**: Never declare completion based solely on code edits. * **Validation Suite**: Always run empirical build checks (`make test`, `npm run build`, `tsc`, or relevant test scripts) before finishing a task. ======================================================================== ## FILE: AGENTS.md (14 lines, 0.9 KiB) ======================================================================== # Agent guide This repository keeps agent guidance in two files, split by kind. Read both before working here. | File | Covers | |---|---| | **[`.agents/AGENTS.md`](.agents/AGENTS.md)** | **Research doctrine** — the guiding principle, the three architectural layers, the epistemological questions, editorial language rules, example-identity rules, and publication quality gates | | **[`CLAUDE.md`](CLAUDE.md)** | **Operations** — layout, authority order, the verification gate, CI, per-layer versioning and changelogs, branch/commit conventions, and research-claim practices | The split is deliberate: doctrine constrains *what may be claimed and how it is written*; operations constrain *how changes are verified and recorded*. Neither substitutes for the other. Start with [`CLAUDE.md`](CLAUDE.md) if you are making a change; start with [`.agents/AGENTS.md`](.agents/AGENTS.md) if you are writing or editing the corpus. ======================================================================== ## FILE: CLAUDE.md (153 lines, 7.8 KiB) ======================================================================== # FCI — agent guide **Foundations of Computational Interaction (FCI)** is a research program for formally describing, measuring, modeling, and predicting human–computer interaction. It is a **research program, not an established discipline**; its scientific necessity and empirical advantage remain to be demonstrated. > **Research doctrine lives in [`.agents/AGENTS.md`](.agents/AGENTS.md)** — the guiding principle, the > three architectural layers, the epistemological questions, editorial language rules, example-identity > rules, and publication quality gates. Read it before touching the corpus. > > **This file is the operational layer**: layout, gates, versioning, and working conventions. --- ## Layout | Path | Role | |---|---| | [`docs/`](docs/) | The conceptual corpus and knowledge system of record | | [`app/`](app/) | Freestanding C11 reference substrate — a *deterministic subset* of the ontology | | [`scripts/`](scripts/) | Repository-level checks that run in CI | | [`.agents/`](.agents/) | Research doctrine for agents | **Authority when artifacts disagree:** [`app/AUTHORITY.md`](app/AUTHORITY.md) is canonical — final synthesis determination, then canonical glossary, then relational ontology, and so on. Code, bibliography records, and generated files **never** silently change theory. --- ## Naming canon - **FCI** is the preferred short name. Avoid institutional phrasing ("the discipline of…"). - **`CIS-EX-NNN` example identifiers are never renamed or renumbered.** Identity stability is a contract: a material semantic change gets a *new* identifier; a correction that restores the documented contract keeps the existing one and updates its validation record. - The `cis_` C namespace is retained under the legacy policy in [`app/NAMING.md`](app/NAMING.md). Residual `cis` symbols are deliberate, not oversights. --- ## Verification gate Run before proposing a merge. CI runs the same commands. ```bash cd app && make test # build + unit, stress, example, schema, benchmark suites python3 scripts/check-doc-links.py # every internal markdown link resolves python3 scripts/check-structure.py # documented directories actually exist ``` ### CI gates | Workflow | What it enforces | |---|---| | `ci.yml` | Builds and tests the substrate under **both gcc and clang**, then asserts the `make conformance` vectors are **byte-identical across compilers**. Plus corpus link and structure integrity. | | `pr-checks.yml` | Per-layer record-keeping; flags multi-layer version bumps that never mention coupling. | **`conclusion` / `conclusion-pr` are the required checks**, not the individual jobs. They assert every dependency *succeeded* — a skipped or cancelled job can never count as green. Making an individual job required instead would let a docs-only PR pass by skipping everything. **Why both compilers.** The substrate claims freestanding C11 determinism. Two builds each passing their own tests does not test that claim; comparing their conformance vectors does. --- ## Versioning — layers move independently FCI versions theory, schemas, software, publication infrastructure, and examples **independently**. A shared number never implies cross-layer conformance. The policy is [`app/VERSIONING.md`](app/VERSIONING.md) and it is **load-bearing, not decorative**: - a theory patch does not require a software release; - a schema release does not imply empirical validation; - passing C tests establishes reference-kernel conformance **only**; - cross-layer compatibility must be **declared in a conformance record** — never inferred from equal version numbers. **Changelogs are per layer, for the same reason.** A single repo-wide changelog would assert exactly the coupling the policy denies. | Layer | Record | |---|---| | Corpus (`docs/`) | [`docs/CHANGELOG.md`](docs/CHANGELOG.md) | | Substrate (`app/`) | [`app/RELEASE_NOTES.md`](app/RELEASE_NOTES.md) | CI reads the **diff** of these files, not merely whether they exist — an untouched changelog is the failure it catches. --- ## Working conventions - **Status honesty.** Never describe something as established unless a record confirms it. Distinguish *documented*, *implemented*, *tested*, and *empirically validated* — they are four different claims. When in doubt, state the weaker one. - **Branch naming.** Named for the work: `feat/…`, `fix/…`, `docs/…`, `chore/…`, `research/…`. Never tool-generated or session-identifier names — branch names are permanent in PR records. - **Git voice.** Normal human engineering prose. **No** `Co-Authored-By`, no AI-attribution trailers, no "generated by" footers, and no agent/assistant references in anything tracked — code, docs, commits, or PRs. - **Don't commit or push unless asked**, except on a feature branch. - **Verify the finish line.** "CI armed" ≠ green; "PR approved" ≠ merged. Check the actual state (`gh pr view --json state`) before reporting completion. --- ## Research practices The empirical protocol this program holds itself to — preregistration, the discovery criterion, negative results, and evidence provenance — is documented in [`docs/90_Project/Research_Practices.md`](docs/90_Project/Research_Practices.md). The short version, because it governs how anything here may be *claimed*: - A claim's **maturity** (how settled) and its **provenance** (what backs it) are separate dimensions. A fixture written against the implementation it was designed alongside cannot falsify that design. - **Negative results are permanent.** A hypothesis that was held and disproven is recorded, not deleted — the abandoned intuition is the thing most likely to be re-proposed later. - **Predictions are registered before the work**, and falsifications keep the lesson they taught. Accuracy is expected to *fall* as scope widens; a rising accuracy with widening scope means the predictions are being written to be safe. --- ## Engineering craft (hard-won — keep these) - **A documented claim that was only ever verified one way is an untested claim.** The substrate's README asserted `make test` "rejects any undefined external symbol." True under GCC; false under Clang, which emits `memcpy` for struct assignment. Both conform — C11 §4 permits a freestanding implementation to require `memcpy`/`memset`/`memmove`/`memcmp`. The invariant is now stated precisely and tested in both directions (a real external dependency is still rejected). - **Fix the diagnostic before the defect.** The first cross-compiler failure printed only `Error 1` — undiagnosable. Making the check *report the offending symbol* came first; guessing would have led to a plausible wrong fix that hid the real question. - **Prose drifts where links do not.** `docs/README.md` described two directories that did not exist and omitted three that did, and the link checker passed the whole time — it validates links, not claims about structure. `scripts/check-structure.py` closes that specific gap; assume other prose claims are unverified until something checks them. - **A gate that cannot fail is not a gate.** After changing a check, prove it still rejects the thing it exists to catch. --- ## Quick map for a new task 1. **Research doctrine, editorial language, example rules** → [`.agents/AGENTS.md`](.agents/AGENTS.md). 2. **Which artifact wins a conflict** → [`app/AUTHORITY.md`](app/AUTHORITY.md). 3. **What may be claimed, and how strongly** → [`docs/90_Project/Research_Practices.md`](docs/90_Project/Research_Practices.md). 4. **Corpus orientation** → [`docs/START_HERE.md`](docs/START_HERE.md). 5. **Building or changing the substrate** → [`app/README.md`](app/README.md), then `make test`. 6. **Adding an executable example** → allocate the next `CIS-EX-NNN`; see `.agents/AGENTS.md` §6.2. 7. Always close with the verification gate above, and record the change in the **layer's own** log. ======================================================================== ## FILE: LICENSE (12 lines, 0.6 KiB) ======================================================================== Foundations of Computational Interaction (FCI) — split licensing (provisional) This repository is licensed under two licenses depending on the artifact: - Code, schemas, and tooling ......... Apache License 2.0 (see LICENSE-CODE) - Research corpus and owned docs ..... CC BY 4.0 (see LICENSE-CONTENT) The authoritative mapping of paths and artifact classes to licenses is in LICENSES.md. Third-party materials are excluded or separately attributed and are NOT relicensed here. This licensing structure is PROVISIONAL and is not final until confirmed against the project's publication and commercialization plans. See LICENSES.md. ======================================================================== ## FILE: LICENSES.md (28 lines, 2.0 KiB) ======================================================================== # Licensing — content-boundary manifest **Status: provisional.** This split-licensing structure is the recommended default and is **not final** until confirmed against publication and commercialization plans. The full canonical license texts (`Apache-2.0`, `CC BY 4.0`) are to be included in `LICENSE-CODE` / `LICENSE-CONTENT` at finalization; until then those files carry the SPDX identifier and the authoritative URL. This manifest is authoritative for **which license governs which path/artifact class**. Where prose in a README and this manifest disagree, this manifest wins. ## Path / artifact-class map | Path or artifact class | License | Notes | |---|---|---| | `app/**` (C source, headers, build, benchmarks, tests) | **Apache-2.0** | Code + patent grant | | `**/*.schema.json` (contract & dataset schemas) | **Apache-2.0** | Executable/enforceable artifacts | | Tooling / scripts (any executable) | **Apache-2.0** | | | `docs/**` prose (`*.md`) authored by the project | **CC BY 4.0** | Research corpus & documentation | | Project-owned figures (`docs/**/Figures/**` authored here) | **CC BY 4.0** | Owned diagrams only | | Bibliographic records / citation metadata (`docs/04_Reference/**`) | mixed / third-party | Metadata about third-party works; not project-licensed. Cite original sources | | Third-party external literature (`docs/03_External_Literature/**`) | **excluded** | Retained under original terms; not relicensed here | | Bundled historical releases (`_archive/**`, `docs/90_Project/Previous_Releases/**`) | inherit-original | Archived byte-for-byte; governed by the terms in effect at their release | | Generated artifacts (`*.pdf`, `*.docx` derived from `*.md`) | inherit-source | Same license as the Markdown source they render | ## Rules - A path not listed here is **unlicensed pending classification** — do not assume permission. - Third-party and excluded material must not be treated as project-licensed even when co-located. - Datasets, figures, and nested archives may each differ from the surrounding directory — check this map, not the folder. ======================================================================== ## FILE: README.md (151 lines, 7.5 KiB) ======================================================================== # Foundations of Computational Interaction (FCI) **FCI** is an interdisciplinary research program for formally describing, measuring, modeling, and predicting human–computer interaction. > It is a **research program, not an established discipline**. Its scientific necessity and empirical > advantage remain to be demonstrated. Nothing here should be read as a validated result unless a > record says so explicitly — and the records are written to make that distinction checkable rather > than rhetorical. --- ## See it run — 30 seconds The smallest complete use of the substrate: declare one bounded state cell, assign semantics to one action, authorize one participant, commit one transition, project the result, print its stable hash. ```bash cd app && make demo && ./build/door # state=1 events=1 hash=8184434590310759885 ``` The **hash is the point**. The same declaration, the same transition, the same number — on any conforming build, under GCC or Clang. That reproducibility is what the corpus is trying to make precise, and it is the one claim here you can check before reading anything. Source: [`app/examples/door.c`](app/examples/door.c) (`CIS-EX-001`). --- ## What is actually here | Layer | Path | What it is | |---|---|---| | **Conceptual corpus** | [`docs/`](docs/) | The knowledge system of record — definitions, research papers, reference material, publication records | | **C reference substrate** | [`app/`](app/) | A freestanding C11 kernel demonstrating computational coherence for a *deterministic subset* of the ontology | | **Corpus tooling** | [`scripts/`](scripts/) | Repository-level checks that run in CI | ### `docs/` — knowledge system of record | Directory | Contents | |---|---| | [`01_Knowledge_System_of_Record/`](docs/01_Knowledge_System_of_Record/) | Canonical definitions, glossary, relational ontology, contract definitions | | [`02_Research_Papers/`](docs/02_Research_Papers/) | Papers in **logical dependency order** — explanandum → primary object → architecture of sciences → representation/projection → ontology & semantics → opportunity → interaction → behavior → measurement → similarity → transfer → strategies | | [`03_External_Literature/`](docs/03_External_Literature/) | Supporting external literature | | [`04_Reference/`](docs/04_Reference/) | Bibliography, dataset schemas, templates, concept graphs, the audit standard | | [`05_Publication/`](docs/05_Publication/) | Publication guidelines and consistency audits | | [`90_Project/`](docs/90_Project/) | Release manifests, audits, decisions, previous release packages, the v1.0 `Reviews/`, [`Research_Practices.md`](docs/90_Project/Research_Practices.md), and the [negative-results registry](docs/90_Project/Negative_Results.md) | Start with **[`docs/START_HERE.md`](docs/START_HERE.md)**. ### `app/` — the C reference substrate A freestanding **C11** kernel plus validation schemas, benchmarks, and stress tests. **What it establishes:** that a deterministic subset of the FCI ontology is computationally coherent — it executes, and its stated invariants hold under test. **What it does not establish** — stated plainly, because the distinction is the point: it does **not** implement or validate the empirical, probabilistic, concurrent, causal, comparative, or predictive framework. Passing these tests is reference-kernel conformance and nothing more. See [`app/README.md`](app/README.md) for the build. --- ## Versioning — layers version independently FCI versions theory, specifications, software, publication infrastructure, and examples **independently**. A shared number never implies cross-layer conformance. | Layer | Version | Stability | |---|---:|---| | FCI theory | 0.5.0 | early; pre-ratification, ontology labels pending identifier ratification | | Contract schemas | 0.2.0 | draft normative candidates | | Dataset schema | 0.3.0 | exploratory, not piloted | | C reference substrate | 0.1.0 | experimental API; no compatibility guarantee before 1.0.0 | | Publication infrastructure | 0.1.0 | internal-use package | | Examples (`CIS-EX-NNN`) | stable identity + independent revision | identity stable; a semantic replacement gets a **new** ID | **Non-coupling is policy, not convention:** a theory patch does not require a software release; a schema release does not imply empirical validation; passing C tests establishes reference-kernel conformance only. Cross-layer compatibility must be *declared in a conformance record* — it is never inferred from equal version numbers. Authoritative policy: [`app/VERSIONING.md`](app/VERSIONING.md). > **On `CIS-EX-*` identifiers.** The program was renamed from "CIS" to FCI, but example identifiers > were deliberately **not** renamed — their stability is the contract. Residual `cis` symbols in the C > substrate are a separate in-flight rename, not an oversight. --- ## Verification gate Run before proposing a merge. CI runs the same commands. ```bash cd app && make test # build + unit, stress, example, schema and benchmark suites python3 scripts/check-doc-links.py # every internal markdown link resolves python3 scripts/check-structure.py # documented directories actually exist ``` `make test` exercises six binaries: substrate unit tests; 8192 deterministic traces with an opportunity-independence check; example generation; 31 JSON schemas with 10 identified contract instances; a state-projection invariant benchmark; and an overclaim-rejection benchmark. CI lives in [`.github/workflows/`](.github/workflows/): | Workflow | Gate | |---|---| | `ci.yml` | Builds and tests the C substrate under **both gcc and clang**, then asserts the `make conformance` vectors are **byte-identical across compilers** — two builds each passing their own tests would not test the determinism claim. Also checks corpus links and that documented directories exist. A mandatory `conclusion` job asserts **every** dependency succeeded — a skipped or cancelled job can never count as green | | `pr-checks.yml` | A PR touching `docs/` must record it in [`docs/CHANGELOG.md`](docs/CHANGELOG.md); a PR touching `app/` must record it in [`app/RELEASE_NOTES.md`](app/RELEASE_NOTES.md) — the per-layer analogue of a single changelog gate | --- ## Changelogs Per-layer, matching the versioning policy: - **Corpus** — [`docs/CHANGELOG.md`](docs/CHANGELOG.md) - **C substrate** — [`app/RELEASE_NOTES.md`](app/RELEASE_NOTES.md) --- ## Licensing Split licensing — [`LICENSES.md`](LICENSES.md) is the authoritative path map. | Material | License | |---|---| | Code, schemas, tooling (`app/`, `scripts/`, `*.schema.json`) | **Apache-2.0** ([`LICENSE-CODE`](LICENSE-CODE)) | | Research corpus, owned documentation and figures (`docs/` prose) | **CC BY 4.0** ([`LICENSE-CONTENT`](LICENSE-CONTENT)) | | Third-party materials | excluded or separately attributed | *Licensing is provisional pending confirmation against publication and commercialization plans.* ## Contributing - **How claims may be made and revised** — [`docs/90_Project/Research_Practices.md`](docs/90_Project/Research_Practices.md) - **Which artifact wins a conflict** — [`app/AUTHORITY.md`](app/AUTHORITY.md) - **Per-layer versioning and non-coupling** — [`app/VERSIONING.md`](app/VERSIONING.md) - **Verification gate** — see above; CI runs the same commands Record every change in the **layer's own** log: corpus changes in [`docs/CHANGELOG.md`](docs/CHANGELOG.md), substrate changes in [`app/RELEASE_NOTES.md`](app/RELEASE_NOTES.md). CI enforces both. ## Citation See [`CITATION.cff`](CITATION.cff). ======================================================================== ## FILE: app/AUTHORITY.md (47 lines, 1.8 KiB) ======================================================================== # FCI Authority and Change Control **Status:** canonical for repository conflict resolution **Version:** 1.0.0 ## Controlling order When artifacts disagree, the first applicable item controls: 1. final synthesis determination; 2. canonical glossary; 3. relational ontology; 4. versioned normative contract schemas; 5. research handbooks and frozen protocols; 6. foundational papers and ratified evidence; 7. formal reference and conformance specifications; 8. reference implementation and tests; 9. identified examples and visualizations; 10. generated derivatives; 11. historical and archived documents. Code does not silently redefine theory. Bibliography records do not define canonical concepts. Generated PDF, DOCX, PNG, SVG, and standalone HTML files are derivatives, not sources of truth. ## Conflict resolution Record the conflict, preserve both claims, and apply the higher-authority artifact until its owner approves a normative change. A lower layer may expose an inconsistency but cannot resolve it by changing meaning. Empirical evidence may trigger review; it does not silently rewrite a frozen definition. ## Supersession and deprecation A superseding artifact must identify its predecessor, effective version, compatibility impact, migration rule, and retained provenance. Deprecated terms remain as aliases only when required to interpret prior records. Archived documents carry a visible non-authoritative status and are never cited as current definitions. ## Corrections and errata Editorial corrections retain version when they restore the documented meaning. Meaning changes follow `VERSIONING.md`, update every dependent source artifact, regenerate derivatives, and add a release note. Published artifacts are immutable: corrections create a new version and an append-only erratum or retraction record. ======================================================================== ## FILE: app/CONCEPT_VALIDATION.md (172 lines, 16.3 KiB) ======================================================================== # Concept Validation Record ## Determination The selected deterministic subset of the Version 1.0.0 concepts forms a coherent minimal computational substrate when four boundaries are enforced: declarations are separate from state, projections are separate from targets, availability is separate from observed action and outcome, and records are separate from interpretations. The C implementation validates those boundaries mechanically. It does not validate the theory empirically. The supplied publication package also establishes limits that affect implementation: - all 54 `canonical_id` cells in `Concept_Source_Matrix.csv` and the corresponding evidence IDs are blank, so no canonical identifier is invented here; - concept-to-source mappings are explicitly heuristic and pending human ratification; - the dataset schema leaves coded events, measures, uncertainty, payload, and state structurally open, so it is unsuitable as a machine execution contract without a normative schema change; - handbooks require provenance, uncertainty, alternative explanations, falsification, and validity evidence, so raw transitions cannot legitimately produce strategy, intention, mechanism, or generalized claims. ## Canonical concept disposition Status meanings: **executed** is a directly implemented and tested primitive; **represented** can be declared or recorded without an inference claim; **research layer** requires a study-specific empirical, interpretive, or normative contract and is deliberately not inferred by the substrate. | Canonical concept | Status | Fundamental treatment | |---|---|---| | Domain commitments | Executed | Bounded variables, actions, predicates, effects, roles, capabilities, and invariants form the explicit domain. | | System state | Executed | A fixed ordered vector of bounded signed 64-bit cells. | | Semantic assignment | Executed | Predicates and effects assign operational transition meaning to action names. | | Semantic state | Represented | Current state under the declared operational semantics; richer content is not inferred. | | Information | Research layer | Typed values and traces are retained; informational meaning or quantity requires a measurement contract. | | Representation | Executed | State and projected state are distinct material structures. | | Projection | Executed | Fields declare source, integer transform, introduced value, and omitted-state mask. | | Scoped invariance | Executed | Typed exact state and projection comparisons require matching field identity, source, transform, and omission scope. | | Interpretation | Research layer | No intention, content, or purpose is inferred from a transition. | | Interaction participant | Executed | Stable bounded participant identity, role, and capability mask. | | Agent | Represented | A participant becomes an acting participant by selecting a declared action; autonomy is not implied. | | Environment | Represented | Declared domain state supplies the bounded action environment. | | Affordance | Research layer | Capability and environmental preconditions are available separately; the relational construct is not collapsed into either. | | Opportunity | Executed | A typed profile coordinates separate availability and trace predicates. | | Opportunity profile | Executed | Domain validity, capability, permission, enablement, target-bound reachability, exposure, signaling, belief, selection, execution, explicit outcome success, tested reversibility, expectation, and uncertainty remain separate fields. | | Capability | Executed | Required and possessed bit sets are checked before transition. | | Permission | Executed | Role authorization is checked independently of capability. | | Enablement | Executed | Current-state preconditions are evaluated independently. | | Reachability | Executed | Bounded breadth-first state search tests existence of an admissible path. | | Exposure | Executed | Projection action mask declares executable access paths. | | Signaling | Executed | A separate projection mask declares perceivable action signals. | | Discoverability | Research layer | Signaling and selection can be observed, but discovery probability and process require a study. | | Believed action | Represented | Availability belief, confidence, and expected consequence are caller-supplied observations. | | Action | Executed | A named table entry joins authorization, preconditions, and effects. | | State transition | Executed | Effects apply to a copy, then bounds and invariants pass before atomic state commit. | | Observation | Represented | Caller-supplied ticks, events, outcomes, and projected snapshots are explicit records. | | Situated behavior | Research layer | Traces support later attribution; behavior is not inferred from action alone. | | Behavioral evidence | Research layer | Formal traces preserve identity, result, outcome, time, and hashes; behavioral evidence additionally requires segmentation, attribution, alternatives, uncertainty, and provenance under a Behavioral Evidence Contract. | | Behavioral equivalence | Research layer | Exact trace comparison is available, but population distributions, task, context, metric, and tolerance require a similarity contract. | | Interactional equivalence | Represented | State, projection, and trace equivalence primitives exist; a complete operation-transition-observation contract is study-specific. | | Interaction | Research layer | State-changing records and an A-B-A pattern can be recovered; coupling, uptake, reciprocal constraint, and the strict interaction criteria require declared evidence. | | Interaction episode | Represented | One system trace is a bounded episode; boundary and timescale are supplied by the embedding study. | | Coupling | Represented | Shared state is the minimal mediating pathway through which participant actions alter later possibilities. | | Perturbation | Represented | A committed effect is the minimal propagated state difference. | | Uptake | Represented | A later transition whose preconditions depend on changed state provides operational uptake evidence. | | Recurrence | Represented | `cis_trace_has_aba_recurrence_pattern` reports only an A-B-A state-changing pattern; coupling and causal closure require declared analysis. | | Interaction contract | Represented | Domain, participants, state, actions, invariants, trace, failure results, reverses, and completion predicates cover the executable core. | | Interaction morphology | Research layer | No rendering or physical surface exists in the substrate. | | Interaction grammar | Executed | Actions, predicate operators, effect operators, and transitions form a modality-independent typed vocabulary. | | Interaction history | Represented | Trace order and participant identity preserve history; learning effects are not inferred. | | Trace | Executed | A fixed-capacity formal trace records selection, rejection or execution, separate outcome, hashes, and time; it is not behavioral evidence by itself. | | Measurement contract | Represented | Primitive timing, frequency, completion, recovery, and mismatch measures require caller-declared interpretation and units. | | Interaction similarity | Represented | State, projection, and trace comparison primitives are typed, use explicit trace identity maps, and return comparability separately. | | Token identity | Executed | One system instance and its monotonic event sequence preserve episode history. | | Type identity | Research layer | Classification rules must be declared by a study; structural resemblance does not establish type identity. | | Equivalence | Executed | Exact equality is returned only inside an explicit state, projection, or trace comparator. | | Similarity | Executed | State range distance, projection field agreement, and correspondence-mapped trace edit distance yield integer permyriad scores. | | Incomparability | Executed | Comparators return `comparable = 0` when shape, provenance kind, omission scope, bounds, or capacity prevents a common space. | | Similarity contract | Represented | Comparator choice supplies the frame; study-level mapping, weights, tolerance, uncertainty, and validity domain remain external declarations. | | Strategy | Research layer | No strategy is inferred from a trace. | | Strategy contract | Research layer | State abstraction, policy, contingencies, rivals, and evidence must be supplied by a study. | | Policy | Represented | A caller can select actions conditionally; the substrate does not learn or infer a policy. | | Fundamental | Executed | Freestanding state, semantics, projection, inspection, snapshots, deterministic hashing, and replay are the implementation's center. | | Foundations of Computational Interaction | Research layer | The substrate makes the program testable; comparative explanatory gain and empirical validity require actual studies. | ## Mechanical validation `tests/test_cis.c` exercises declaration validation, duplicate identity rejection, capability and permission separation, enablement, atomic bounds rejection, monotonic time, explicit success outcomes, replay and divergence detection, projection provenance and omission, bounded reachability, opportunity mismatch, reversibility, recurrence, recovery timing, state/projection/trace comparison, and measurements. The production object is compiled freestanding with builtin and stack-protector calls disabled. `make test` checks it with `nm` and fails if any external symbol remains. The implementation has no allocation, I/O, clock, filesystem, network, operating system, or third-party call. Hosted I/O exists only in the demo and test driver. ## Further test findings and resolutions | Finding | Conflict with Version 1.0 | Resolution | |---|---|---| | Reachability defaulted to enablement when no target was supplied. | Enablement is a current-state precondition relation; reachability requires a declared target, constraints, and horizon. | Opportunity evaluation now requires a target predicate and always runs bounded reachability. | | Declaring a reverse action was treated as proof of reversibility. | Reversibility is an outcome relation, not metadata presence. | The engine now executes the forward and reverse semantics under the same participant authority and requires exact restoration of the prior state. | | Projected snapshots discarded field identity and transformation provenance. | Similarity and invariance require an explicit correspondence and preserved/transformed/introduced/omitted structure. | Projected snapshots now retain complete field declarations; incompatible names, sources, transforms, kinds, or omission masks are incomparable. | | Trace edit distance assumed equal numeric participant and action indices had equal meaning. | Interaction similarity requires a declared correspondence mapping. | Trace comparison now requires participant and action identity maps and refuses comparison without them. | | An A-B-A event pattern was reported as recurrence. | Temporal order alone does not establish coupling, uptake, or causal return influence. | The API now reports only the exact state-changing A-B-A recurrence pattern; causal recurrence remains a research-layer determination. | | Recovery measurement replayed actions without checking trace hashes. | Behavioral evidence must preserve provenance and reject divergent records. | Recovery measurement now validates every before/after hash and returns replay divergence on tampering. | | Execution was initially treated as successful outcome. | Selected, executed, and successful are distinct trace predicates. | Outcome is now an explicit, separately recorded success, failure, or unknown value. | | The interactive profile rendered an unobserved outcome like a failed outcome. | Unknown evidence is not negative evidence; execution and success remain separate. | The successful dimension is now tri-valued: yes after explicit success, no after explicit failure, and unknown when no outcome is observed. | | The interactive summary collapsed system executability into projection exposure. | Capability, permission, enablement, exposure, and belief are different relations. | The figure now reports system executability, projected availability, and belief alignment as three separate conclusions before showing their component dimensions. | | Draft 0.1.0 contracts named evidence boundaries without requiring all fields needed to reproduce them. | A contract cannot govern a claim when host modality, episode identity, coding lineage, interpretation, uncertainty, counterfactual, abstention, or comparison evidence may be omitted. | Contract schemas 0.2.0 require the missing reproduction boundaries; all ten CIS-EX-008 instances, explanatory templates, synthetic references, validators, and FIG-002 migrate together. | | The initial contract-instance test checked field names but accepted any declared contract version. | Versioned draft schemas require exact instance-to-schema alignment. | The dependency-free validator now requires schema and contract version 0.2.0 for every identified CIS-EX-008 contract instance. | The deterministic stress suite executes and replays 8,192 bounded traces across successful and rejected transitions, then independently varies capability, permission, enablement, reachability, exposure, signaling, and belief. This specifically guards against recombining the opportunity dimensions corrected above. ## Experiential validation definition The interactive door model, identified as **CIS-EX-003**, is a second, inspectable execution of the same minimal domain used by the C tests: two bounded state cells, four table-defined actions, three participants with distinct role/capability combinations, projection-controlled exposure and signaling, target-bound reachability, explicit belief, and separately recorded selection, execution, and outcome. Every visual state is hashed with the same byte order and FNV-1a procedure as `cis_state_hash`. The four **CIS-EX-002** expected values are generated by `make conformance` from the freestanding C object and asserted as golden vectors by `tests/test_cis.c`. A live parity failure is therefore visible in the model rather than hidden in presentation. The visual trace is an experiential aid, not behavioral evidence and not an empirical validation of discoverability, strategy, affordance, uptake, or causal recurrence. The complete example identity, controls, expected behavior, exercised concepts, and non-claims are defined in `examples/README.md`. Browser checks exercised successful and rejected transitions, atomic rejection, success remaining false for an unknown outcome, explicit success annotation, capability/permission/enablement/reachability separation, all four C state hashes, the 320–620 pixel reflow boundary, horizontal overflow, and console diagnostics. Successive CIS-EX-003 visual reviews found a flat control hierarchy, an undifferentiated opportunity tile matrix, excessive empty trace space, decorative active-state color, and a summary that obscured the boundary between execution, projection, belief, and unknown outcome. The corrected figure leads with three plain-language conclusions, groups the paper's analytical layers, replaces the tile matrix with compact evidence rows, preserves unknown explicitly, uses one state surface, and retains accessible labels without hover titles. CIS-EX-004 and CIS-EX-005 extend experiential validation to the two boundaries not made visually primary by CIS-EX-003: governed projection comparison and the eight measurement evidence levels. Their exact canonical concept, source-key, interaction, and non-claim alignments are maintained in `examples/PAPER_ALIGNMENT.md`. CIS-EX-008 extends structural validation through a complete draft contract chain: two Projection instances, Opportunity, Interaction, Behavioral Evidence, and five Measurement instances. A positive synthetic study fixture demonstrates the bounded record-to-measure lineage; a negative fixture proves that a required environment cannot be silently omitted. These fixtures establish schema and lineage behavior only, not empirical validity or authorization to collect participant data. ## Falsification boundary This artifact would fail its fundamental claim if replay diverged from an untampered trace, a rejected transition mutated state, a projection obscured whether structure was omitted or introduced, any opportunity dimension implied another without an explicit rule, comparison reported equivalence across incompatible shapes, capacity exhaustion were silent, or the library object acquired an external symbol. Those conditions are executable failures rather than interpretive judgments. ======================================================================== ## FILE: app/CONFORMANCE.md (61 lines, 2.5 KiB) ======================================================================== # FCI Conformance Specification 0.1.0 Conformance is layered. No layer inherits another layer's status. ## Levels ### T — Theory alignment An artifact states FCI 1.0.0 interdisciplinary-synthesis determination, uses the canonical ontology labels, distinguishes analytical dependency from causal direction, and makes no disciplinary-independence claim. ### C — Contract conformance An artifact validates against a named contract schema version and records the contract instance identifier, version, authority, scope, and prohibited interpretations. Draft 0.x schema validation is not contract ratification. ### D — Dataset conformance A dataset validates against `interaction_study.schema.json` 0.3.0, resolves all referenced records, preserves evidence lineage, declares missingness and uncertainty, and identifies immutable protocol and contract versions. ### R — Deterministic reference-kernel conformance An implementation matches the selected deterministic semantics exercised by the C golden tests: bounded scalar state, deterministic predicates and effects, atomic invariant-preserving commit, projections, opportunity dimensions, bounded reachability, formal traces, replay, and typed comparisons. R conformance does not include OEPLTS probability, observation and instrument channels, coupling semantics, concurrency, composition, participant-local state, belief distributions, strategy, causality, prediction, or empirical measurement validity. ### E — Empirical protocol conformance A study has preregistered and frozen relevant contracts, instruments, coding, exclusions, uncertainty, analysis, alternatives, falsification conditions, and data governance. No study in this repository currently claims E conformance. ### P — Publication readiness References and evidence mappings are authority-verified and reviewed, figures have rights and accessibility records, schemas are piloted, and all generated derivatives match sources. The current repository does not claim P conformance. ## Required conformance statement Every release or study must list each claimed level, exact version, evidence, known exclusions, and reviewer status. Silence means no claim. Passing a lower-level check never licenses a higher-level claim. In particular: - computation is not empirical validation; - schema validity is not measurement validity; - a formal trace is not behavioral evidence; - prediction output is not calibration or transport evidence; - an A-B-A state-changing pattern is not reciprocal causal closure; - polished derivatives are not publication readiness. ======================================================================== ## FILE: app/DOCUMENT_MAP.md (35 lines, 4.0 KiB) ======================================================================== # Canonical Document Map **Map version:** 0.1.0 **Review status:** internal consolidation; external reviewers unassigned | Document ID | Artifact | Role | Version | Status | Depends on | Reviewer | |---|---|---|---:|---|---|---| | COMPINT-DET-001 | `README.md` supported determination | canonical determination | 1.0.0 | frozen | final synthesis | unassigned | | COMPINT-AUTH-001 | `AUTHORITY.md` | canonical governance | 1.0.0 | frozen | determination | unassigned | | COMPINT-GLOSS-001 | `../docs/01_Knowledge_System_of_Record/02_Glossary/Computational_Interaction_Science_Glossary_v0.4.md` | canonical vocabulary | 0.4 | provisional system of record | research corpus | unassigned | | COMPINT-ONTO-001 | `../docs/01_Knowledge_System_of_Record/01_Ontology/Current/A_Relational_Ontology_of_Computational_Interaction_v0.3.md` | canonical relational ontology | 0.3 | provisional | glossary | unassigned | | COMPINT-ONTO-ARCH-001 | `../docs/90_Project/Previous_Releases/Computational_Interaction_Science_Canonical_Corpus_v1.0.0.zip` | historical provenance | 0.1 | archived/superseded | none | not applicable | | COMPINT-ENC-001 | `../docs/01_Knowledge_System_of_Record/03_Encyclopedia/Computational_Interaction_Science_Encyclopedia_Article_Draft_v0.3.md` | supporting public synthesis | 0.3 | draft | glossary; ontology | unassigned | | COMPINT-LIMITS-001 | `../docs/02_Research_Papers/13_Formal_Models/The_Limits_of_Computational_Interaction_Models_v0.2.md` | supporting limits paper | 0.2 | draft | determination; ontology | unassigned | | COMPINT-INVAR-001 | `../docs/02_Research_Papers/04_Representation_and_Projection/Scoped_Invariance_Under_Projection_v0.4.md` | supporting concept paper | 0.4 | draft | ontology; comparison contract | unassigned | | COMPINT-FUND-001 | `../docs/01_Knowledge_System_of_Record/04_Framework/Fundamental_and_Computational_Interaction_Science_v0.4.md` | supporting implementation relationship | 0.4 | draft | ontology; conformance | unassigned | | COMPINT-WIKI-001 | `../docs/01_Knowledge_System_of_Record/07_Reviews/Computational_Interaction_Science_Wikipedia_Readiness_Review_v0.2.md` | publication constraint | 0.2 | current review memo | encyclopedia article | unassigned | | COMPINT-CONTRACT-* | `docs/04_Reference/Templates/*.schema.json` — per-type IDs, see [Contract ID Registry](../docs/01_Knowledge_System_of_Record/05_Specifications/Contracts/Contract_ID_Registry.md) | draft normative contract system; `COMPINT-CONTRACT-001` retained as deprecated family alias | 0.2.0 | candidate | glossary; ontology | unassigned | | COMPINT-DATA-001 | `docs/04_Reference/Dataset_Schema/interaction_study.schema.json` | exploratory interchange schema | 0.3.0 | candidate | contracts | unassigned | | COMPINT-CONFORM-001 | `CONFORMANCE.md` | normative conformance boundary | 1.0.0 | frozen | authority; contracts | unassigned | | COMPINT-KERNEL-001 | `include/cis.h`; `src/cis.c` | deterministic reference subset | 0.1.0 | experimental | conformance | tests | | COMPINT-EXAMPLES-001 | `examples/manifest.csv` | example registry | 1.0.0 theory alignment | active | kernel; contracts | tests | | COMPINT-PUB-001 | `docs/` publication infrastructure | supporting release package | 0.1.0 | internal only | all source artifacts | unassigned | | COMPINT-EXPLAIN-001 | `docs/EXPLAINING_COMPINT.md` | supporting conceptual introduction | 0.1.0 | active | determination; ontology; examples | unassigned | No `/research` directory is present in this checkout, so a paper-by-paper research index cannot be truthfully generated here. The figure catalog records 16 source-paper entries from the supplied corpus, but the cited source DOCX paths are absent. Restoring and reviewing that corpus is a release blocker; the map does not invent paper files or statuses. Generated `.pdf`, `.docx`, `.png`, `.svg`, `.html`, `.zip`, and spreadsheet artifacts are derivatives unless a row above explicitly designates otherwise. Duplicate canonical documents have not been created; the archived ontology is retained solely for provenance. ======================================================================== ## FILE: app/Makefile (141 lines, 6.5 KiB) ======================================================================== CC ?= cc CFLAGS ?= -std=c11 -O2 -Wall -Wextra -Wpedantic -Werror CPPFLAGS ?= -Iinclude FREESTANDING_FLAGS := -ffreestanding -fno-builtin -fno-stack-protector BUILD := build LIB_OBJECT := $(BUILD)/cis.o .PHONY: all test demo conformance benchmarks verify-object verify-examples clean all: verify-examples $(BUILD)/libcis.a $(BUILD)/test_cis $(BUILD)/test_stress $(BUILD)/test_examples $(BUILD)/test_schemas $(BUILD)/door $(BUILD)/projection-benchmark $(BUILD)/overclaim-benchmark $(BUILD): mkdir -p $(BUILD) $(LIB_OBJECT): src/cis.c include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) $(FREESTANDING_FLAGS) -c src/cis.c -o $@ $(BUILD)/libcis.a: $(LIB_OBJECT) ar rcs $@ $^ $(BUILD)/test_cis: tests/test_cis.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) tests/test_cis.c $(LIB_OBJECT) -o $@ $(BUILD)/test_stress: tests/test_stress.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) tests/test_stress.c $(LIB_OBJECT) -o $@ $(BUILD)/test_examples: tests/test_examples.c | $(BUILD) $(CC) $(CFLAGS) tests/test_examples.c -o $@ $(BUILD)/test_schemas: tests/test_schemas.c | $(BUILD) $(CC) $(CFLAGS) tests/test_schemas.c -o $@ $(BUILD)/door: examples/door.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) examples/door.c $(LIB_OBJECT) -o $@ $(BUILD)/conformance: examples/conformance.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) examples/conformance.c $(LIB_OBJECT) -o $@ $(BUILD)/projection-benchmark: examples/benchmarks/projection-benchmark.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) examples/benchmarks/projection-benchmark.c $(LIB_OBJECT) -o $@ $(BUILD)/overclaim-benchmark: examples/benchmarks/overclaim-benchmark.c $(LIB_OBJECT) include/cis.h | $(BUILD) $(CC) $(CPPFLAGS) $(CFLAGS) examples/benchmarks/overclaim-benchmark.c $(LIB_OBJECT) -o $@ # C11 §4 permits a freestanding implementation to require memcpy, memset, memmove and memcmp; # both GCC and Clang document emitting these as implicit libcalls even under -ffreestanding # -fno-builtin. Clang emits `memcpy` for struct assignment where GCC inlines it, so requiring # ZERO undefined symbols encodes a claim STRONGER than "freestanding" and one that is not # portably achievable without shipping our own implementations of the four. # # This allowlist is a precisification, not a relaxation: any symbol outside these four still # fails, which is what the check exists to catch. Providing substrate-local implementations # would restore the stricter zero-symbol property and is the available stronger option. FREESTANDING_ALLOWED := memcpy memset memmove memcmp verify-object: $(LIB_OBJECT) @undef="$$(nm -u $(LIB_OBJECT) | awk '{print $$NF}' | sed 's/^_//')"; \ unexpected=""; \ for sym in $$undef; do \ case " $(FREESTANDING_ALLOWED) " in \ *" $$sym "*) ;; \ *) unexpected="$$unexpected $$sym" ;; \ esac; \ done; \ if [ -n "$$unexpected" ]; then \ echo "verify-object: FAILED — $(LIB_OBJECT) references external symbols beyond the"; \ echo " four the C standard permits a freestanding implementation to require:"; \ for sym in $$unexpected; do echo " $$sym"; done; \ echo " (compiler: $(CC); permitted: $(FREESTANDING_ALLOWED))"; \ exit 1; \ fi; \ if [ -n "$$undef" ]; then \ echo "verify-object: freestanding invariant holds ($(CC)) — implicit libcalls only:$$(echo $$undef | sed 's/^/ /')"; \ else \ echo "verify-object: freestanding invariant holds ($(CC)) — no undefined symbols at all"; \ fi verify-examples: test -f examples/manifest.csv test -f examples/README.md test -f examples/visualizations/src/interaction-substrate-lab.html test -f examples/visualizations/interaction-substrate-lab.html test -f examples/visualizations/src/projection-invariance-workbench.html test -f examples/visualizations/projection-invariance-workbench.html test -f examples/visualizations/src/evidence-inference-ladder.html test -f examples/visualizations/evidence-inference-ladder.html test -f ../docs/04_Reference/Figures/FIG-001_Concept_Dependency_Graph.dot test -f ../docs/04_Reference/Figures/FIG-001_Concept_Dependency_Graph.svg test -f ../docs/04_Reference/Figures/FIG-001_Concept_Dependency_Graph.png test -f ../docs/04_Reference/Figures/FIG-001_Concept_Dependency_Graph.pdf test -f ../docs/04_Reference/Figures/FIG-002_Contract_Architecture.dot test -f ../docs/04_Reference/Figures/FIG-002_Contract_Architecture.svg test -f ../docs/04_Reference/Figures/FIG-002_Contract_Architecture.png test -f ../docs/04_Reference/Figures/FIG-002_Contract_Architecture.pdf grep -q 'CIS-EX-001' examples/door.c grep -q 'CIS-EX-002' examples/conformance.c grep -q 'CIS-EX-003' examples/visualizations/src/interaction-substrate-lab.html grep -q 'CIS-EX-003' examples/visualizations/interaction-substrate-lab.html grep -q 'CIS-EX-004' examples/visualizations/src/projection-invariance-workbench.html grep -q 'CIS-EX-004' examples/visualizations/projection-invariance-workbench.html grep -q 'CIS-EX-005' examples/visualizations/src/evidence-inference-ladder.html grep -q 'CIS-EX-005' examples/visualizations/evidence-inference-ladder.html grep -q 'CIS-EX-006' examples/benchmarks/projection-benchmark.c grep -q 'CIS-EX-007' examples/benchmarks/overclaim-benchmark.c grep -q 'CIS-EX-008' examples/studies/CIS-EX-008_projection-signaling-study.md grep -q 'CIS-EX-001' examples/README.md grep -q 'CIS-EX-002' examples/README.md grep -q 'CIS-EX-003' examples/README.md grep -q 'CIS-EX-004' examples/README.md grep -q 'CIS-EX-005' examples/README.md grep -q 'CIS-EX-006' examples/README.md grep -q 'CIS-EX-007' examples/README.md grep -q 'CIS-EX-008' examples/README.md grep -q 'CIS-EX-003' examples/PAPER_ALIGNMENT.md grep -q 'CIS-EX-004' examples/PAPER_ALIGNMENT.md grep -q 'CIS-EX-005' examples/PAPER_ALIGNMENT.md grep -q 'CIS-EX-006' examples/PAPER_ALIGNMENT.md grep -q 'CIS-EX-007' examples/PAPER_ALIGNMENT.md grep -q 'CIS-EX-008' examples/PAPER_ALIGNMENT.md test: verify-object verify-examples $(BUILD)/test_cis $(BUILD)/test_stress $(BUILD)/test_examples $(BUILD)/test_schemas $(BUILD)/projection-benchmark $(BUILD)/overclaim-benchmark ./$(BUILD)/test_cis ./$(BUILD)/test_stress ./$(BUILD)/test_examples ./$(BUILD)/test_schemas ./$(BUILD)/projection-benchmark ./$(BUILD)/overclaim-benchmark demo: $(BUILD)/door ./$(BUILD)/door conformance: $(BUILD)/conformance ./$(BUILD)/conformance benchmarks: $(BUILD)/projection-benchmark $(BUILD)/overclaim-benchmark ./$(BUILD)/projection-benchmark ./$(BUILD)/overclaim-benchmark clean: rm -rf $(BUILD) ======================================================================== ## FILE: app/NAMING.md (34 lines, 1.4 KiB) ======================================================================== # Naming Policy **Formal name:** Foundations of Computational Interaction **Preferred short name:** FCI **Supported determination:** interdisciplinary scientific synthesis and research program, not an established independent scientific discipline Use **FCI** in repository prose, schema titles, examples, and new public interfaces. Use **Foundations of Computational Interaction** on first formal mention. The existing C namespace (`cis_`, `Cis*`, `CIS_*`) is a Version 0.1 legacy namespace retained to avoid a cosmetic API rewrite during consolidation. It does not denote a separate project or stronger disciplinary claim. A future stable library namespace should use `compint_` after an API design and migration plan are ratified; aliases must not create two permanent systems of record. `Agent` is subordinate to the general ontology: ```text Interaction Participant └── Acting Participant └── Agent ├── AI Agent └── Autonomous Agent ``` Use `Interaction Participant` for the general category. Use `Agent` only when action selection through a policy, rule, control process, intention, or related organization is specifically in scope. Use `formal trace`, `execution record`, or `instrument record` for C events. Reserve `behavioral evidence` for records processed under an instantiated Behavioral Evidence Contract with segmentation, attribution, alternatives, uncertainty, and provenance. ======================================================================== ## FILE: app/README.md (132 lines, 7.8 KiB) ======================================================================== # Bounded Reference Substrate for Computational Interaction Foundations of Computational Interaction is an interdisciplinary scientific program for describing, measuring, comparing, modeling, and predicting human-computer interaction. It coordinates established theories and methods around computational interaction as a shared explanatory object, framing the work as a foundational model rather than a proposal for a new academic field. This repository implements a deterministic, fixed-capacity reference kernel for a selected subset of FCI's ontology. It demonstrates separability and internal computational coherence; it does not implement or validate the complete empirical, probabilistic, concurrent, causal, comparative, or predictive framework. For a plain-language walkthrough, start with [`../docs/04_Reference/Handbooks/Explaining_CompInt.md`](../docs/04_Reference/Handbooks/Explaining_CompInt.md), then use the example implementation files to test each distinction directly. ## What it validates The model keeps the research's main analytical layers separate: - **domain commitments** are explicit state-variable, action, transition, invariant, participant, and role declarations; - **system state** is a bounded vector of signed 64-bit cells; - **operational semantics** are ordered predicates and effects; - **projections** explicitly label preserved, transformed, introduced, and omitted structure and separately expose and signal actions; - **opportunity** reports domain validity, capability, permission, enablement, reachability, exposure, signaling, belief, selection, execution, success, and reversibility as separate fields; - **interaction** is retained as an event trace with participant identity, before and after state hashes, failures, and an exact ABA recurrence-pattern test that makes no causal claim; - **snapshots and replay** use a deterministic canonical integer encoding; - **comparison** includes typed exact state/projection equivalence, normalized state similarity, and trace edit similarity under an explicit identity correspondence; - **measurement** includes timing, frequency, completion, opportunity mismatch, and recovery primitives without treating any metric as a construct. The implementation does not claim empirical construct validation. It validates that the concepts can form a coherent, deterministic computational substrate. Strategy, interpretation, behavioral attribution, and generalized claims remain evidence-bearing research layers and are not inferred from raw actions. ## Authority order When artifacts disagree, resolve them in this order: 1. final synthesis determination; 2. canonical glossary; 3. relational ontology and `docs/CANONICAL_ONTOLOGY.md` synchronization freeze; 4. versioned normative contract schemas; 5. research handbooks and protocols; 6. individual foundational papers and ratified evidence; 7. `CONFORMANCE.md` and the computational reference specification; 8. C implementation and tests; 9. examples and visualizations; 10. generated PDF, DOCX, PNG, SVG, and standalone HTML derivatives; 11. historical or archived documents. Code never silently defines theory. Bibliography records never define canonical concepts. Generated derivatives are never edited as sources. ## Build and run ```sh make make test make demo make conformance make benchmarks ``` These commands require only a C11 compiler and `make`. The library itself uses only the C standard headers for fixed-width integer and size types; it performs no I/O, allocation, filesystem, clock, network, or operating-system calls. The library object is compiled as freestanding code, and `make test` rejects any undefined external symbol in it other than the four the C standard permits a freestanding implementation to require (`memcpy`, `memset`, `memmove`, `memcmp`). Cross-compiler CI showed why the distinction matters: GCC inlines the struct copies in this substrate and emits none of them, while Clang emits `memcpy`. Both are conforming, so a zero-undefined-symbol claim is stronger than "freestanding" and is not portably achievable without shipping our own implementations of those four. The demo and test executables use hosted C only to print their results. ## Layout - `include/cis.h` — complete public data model and operations - `src/cis.c` — dependency-free implementation - `tests/test_cis.c` — executable research-concept validation - `tests/test_stress.c` — deterministic state-machine and opportunity stress tests - `tests/test_examples.c` — example identity and generated-output synchronization - `tests/test_schemas.c` — dependency-free JSON syntax and local-reference validation - `examples/README.md` — stable identifiers and complete contracts for every example - `examples/manifest.csv` — machine-readable example identity registry - `examples/door.c` — CIS-EX-001, smallest end-to-end interaction - `examples/conformance.c` — CIS-EX-002, C-generated state/hash vectors - `examples/benchmarks/projection-benchmark.c` — CIS-EX-006, cross-interface projection test - `examples/benchmarks/overclaim-benchmark.c` — CIS-EX-007, incapable-action overclaim test - `examples/visualizations/interaction-substrate-lab.html` — CIS-EX-003, self-contained experiential model - `examples/visualizations/projection-invariance-workbench.html` — CIS-EX-004, governed projection comparison - `examples/visualizations/evidence-inference-ladder.html` — CIS-EX-005, measurement evidence boundary - `examples/PAPER_ALIGNMENT.md` — canonical concept, source-key, and claim alignment - `CONCEPT_VALIDATION.md` — disposition and validation boundary for all 54 concepts - `../docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Ontology.md` — frozen theory determination and ontology labels - `../docs/04_Reference/Handbooks/Explaining_CompInt.md` — plain-language conceptual walkthrough - `CONFORMANCE.md` — layered theory, schema, implementation, and empirical claims - `VERSIONING.md` — independent version lines and compatibility rules - `NAMING.md` — FCI terminology and legacy C namespace policy - `AUTHORITY.md` — conflict, supersession, deprecation, and errata control - `DOCUMENT_MAP.md` — canonical/supporting/historical artifact registry - `../docs/01_Knowledge_System_of_Record/10_Governance/` — research data and protocol governance minimum ## Deliberate limits Capacities are compile-time constants, names are bounded byte arrays, time is an unsigned caller-supplied tick, and values are signed 64-bit integers. Reachability is bounded breadth-first search. Projection transforms use integer multiply/add. These limits avoid hidden allocation and numerical behavior and make exhaustion a typed error. Increasing a capacity changes storage only, not semantics. Canonical concept identifiers in the supplied `Concept_Source_Matrix.csv` and `Evidence_Register.csv` are blank. This implementation therefore uses descriptive C identifiers and does not invent authoritative canonical IDs. The C representation is deliberately bounded to 16 state variables, 16 actions, 16 participants, 128 trace records, 128 reachability states, and a 16-step horizon. Roles and capabilities use 32-bit masks; predicates are scalar comparisons; effects are `SET` and `ADD`; projections are affine integer fields; belief is caller-supplied; and no serialization, wire format, thread safety, probability, or concurrency semantics are claimed. A production formal specification must not be created by merely increasing these constants. The public header identifies API version 0.1.0 and trace schema version 1. Execution records carry that trace version, and replay rejects an incompatible version. No stable serialization format exists; in-memory structure layout is not a wire format or compatibility guarantee. Independent systems require external synchronization because the mutable API is not thread-safe. ======================================================================== ## FILE: app/RELEASE_NOTES.md (61 lines, 3.5 KiB) ======================================================================== # Release notes — C reference substrate The substrate versions **independently** of the theory layer (currently 0.5.0). Passing these tests establishes reference-kernel conformance only. See [`VERSIONING.md`](VERSIONING.md). # Unreleased _Nothing yet._ # 0.1.0 — 2026-07-20 First versioned release of the substrate. Experimental API; no compatibility guarantee before 1.0.0. - `VERSIONING.md`: the FCI theory layer is relabelled **0.5.0** (was 1.0.0), with the rationale recorded in the policy itself. Substrate, schema, dataset and publication versions are **unchanged** — this is a single-layer correction, and per the non-coupling rules it implies nothing about any other layer. - `verify-object` now permits exactly the four external symbols C11 §4 allows a freestanding implementation to require (`memcpy`, `memset`, `memmove`, `memcmp`) and rejects everything else. This is a **precisification, not a relaxation**: cross-compiler CI found that GCC inlines this substrate's struct copies while Clang emits `memcpy`, so the previous zero-undefined-symbol assertion encoded a claim stronger than "freestanding" that no portable build can satisfy. Verified that the check still rejects a genuine external dependency. The stronger property is still available by shipping substrate-local implementations of the four; that option is recorded in the Makefile rather than taken silently. - `app/README.md` corrected: it claimed `make test` rejects *any* undefined external symbol, which was true only under GCC. - `verify-object` now reports **which** undefined symbols were found, and under which compiler, instead of failing silently via `test -z`. The freestanding invariant is a real claim about the substrate; a gate that asserts it without saying what broke is not diagnosable. CI's first cross-compiler run failed here under Linux clang with no usable log output — this is the fix for that, not a relaxation of the check. # FCI Internal Consolidation Candidate 1.0.0 This candidate freezes the interdisciplinary-synthesis determination, authority order, naming policy, ontology labels, conformance levels, and C reference scope. It adds draft contract and modular dataset schemas, governance controls, machine-generated ontology and contract figures, two deterministic benchmarks, and one proposed study protocol. CIS-EX-008 now includes ten complete draft contract instances plus positive and negative synthetic dataset fixtures for the record-to-measure lineage. Contract schemas 0.2.0 make the previously implicit reproduction boundaries structurally mandatory: projection host and feedback, action vocabulary and consequences, interaction identity and provenance, behavioral coding lineage, measurement interpretation and uncertainty budgets, and the complete similarity, transfer, strategy, prediction, and comparison claim boundaries. The ten CIS-EX-008 instances and synthetic contract references migrate with the schema; theory remains 1.0.0. Breaking draft changes: dataset schema 0.3.0 requires environments and explicit participant consent references; the C execution record adds trace schema version 1 and replay rejects incompatible versions; the recurrence helper is named `cis_trace_has_aba_recurrence_pattern`. External release remains blocked by concept-ID ratification, authoritative bibliography and evidence review, schema pilots, derivative regeneration, empirical work, and independent technical, methods, accessibility, and ethics/community review. No publication date or reviewer is assigned. ======================================================================== ## FILE: app/VERSIONING.md (40 lines, 2.5 KiB) ======================================================================== # Versioning Policy FCI versions theory, specifications, software, publication infrastructure, and examples independently. A shared number never implies cross-layer conformance. | Layer | Current version | Stability | Compatibility rule | |---|---:|---|---| | FCI theory | 0.5.0 | early; pre-ratification, ontology labels pending identifier ratification | Patch clarifies without changing commitments; minor adds backward-compatible theory; major changes commitments. | | Contract schemas | 0.2.0 | draft normative candidates | Any incompatible field, meaning, or validation change increments minor until 1.0.0. | | Dataset schema | 0.3.0 | exploratory, not piloted | Breaking record or reference changes increment minor until 1.0.0. | | C reference substrate | 0.1.0 | experimental API | No compatibility guarantee before 1.0.0; every breaking change is recorded. | | Publication infrastructure | 0.1.0 | internal-use package | Derivatives must identify their source release; metadata verification is independent. | | Examples | stable `CIS-EX-NNN` identity plus independent revision | identity stable; behavior contract explicit | Semantic replacement gets a new ID; corrections retain ID and update validation. | ## On the 0.5.0 label The theory layer carried **1.0.0**, then briefly **0.9.0**. Neither was ever tagged or published. `1.0.0` claimed a ratification that has not occurred — ontology labels remain pending identifier ratification, and the program's own stance is that its scientific necessity and empirical advantage remain to be demonstrated. `0.9.0` still implied *approaching release*, which overstates how settled the theory is. **0.5.0** is the honest position: substantial work exists, and it is nowhere near a stable commitment. **No theory content changed by either correction.** These are relabellings, not revisions. Records elsewhere citing "theory 1.0.0" — example alignment records, prior release notes, editorial reports — refer to the same content under a former label and are deliberately left unedited: rewriting them would misstate what was validated when. ## Non-coupling rules - A theory patch does not automatically require a software release. - A schema release does not imply empirical validation. - Passing C tests establishes reference-kernel conformance only. - Updating bibliography metadata does not change theory. - Generated PDF, DOCX, PNG, and HTML derivatives inherit their source version and never control it. - Compatibility across layers must be declared in a conformance record; it is never inferred from equal version numbers. ======================================================================== ## FILE: app/examples/PAPER_ALIGNMENT.md (32 lines, 4.3 KiB) ======================================================================== # Example-to-Research Alignment This register prevents an interactive figure from becoming a visual metaphor that exceeds the Version 1.0.0 research. Definitions and source keys come from `docs/02_Citation_Evidence/Citation_Map.md` and `Concept_Source_Matrix.csv`. The package labels those source mappings corpus-derived and heuristic; the keys below are alignment candidates, not ratified evidence claims. | Example | Primary canonical concepts | Internal research basis | Candidate source keys | Figure claim boundary | |---|---|---|---|---| | CIS-EX-003 | system state; participant; capability; permission; enablement; reachability; exposure; signaling; believed action; opportunity profile; action; transition; trace; reversibility | Citation Map; Experimental Handbook opportunity protocol; Measurement Handbook evidence separation | `gibson1979`; `sandhu1996`; `ferraiolo2003`; `vanderaalst2016`; `fipa2002`; `park1981`; `taylor1994` | Demonstrates that availability and trace predicates can vary independently. It does not establish affordance, discovery, uptake, causal recurrence, behavior, or strategy. | | CIS-EX-004 | representation; projection; scoped invariance; equivalence; similarity; incomparability; similarity contract | Citation Map projection contract and typed invariance definitions; Experimental Handbook comparison protocol | `tarski1944`; `cousot1977`; `gentner1983`; `gower1971`; `taylor1994`; `zhang1994` | Demonstrates preservation, transformation, omission, introduction, and typed comparison under an explicit field correspondence. It refuses overall equivalence from partial preservation. | | CIS-EX-005 | observation; behavioral evidence; measurement contract; trace; construct evidence; mechanism evidence; generalized claim | Measurement Handbook governing rule and eight evidence levels; Experimental Handbook separation of records, events, behavior, latent constructs, and conclusions | `stevens1946`; `taylor1994`; `cronbach1955`; `yarkoni2017`; `suppes1963` | Demonstrates that evidence levels require cumulative gates. It never derives intention, mechanism, construct validity, or transport from a raw event alone. | | CIS-EX-006 | representation; projection; exposure; signaling; opportunity profile; scoped invariance; typed comparison | Projection contract; Citation Map representation and opportunity definitions; Experimental Handbook comparison protocol | `cousot1977`; `gentner1983`; `gower1971`; `zhang1994`; `gibson1979` | Demonstrates exact semantic-state projection equivalence alongside an intentional signaling difference. It does not establish interface, behavior, interaction, accessibility, usability, or outcome equivalence. | | CIS-EX-007 | participant; capability; permission; exposure; signaling; belief; selection; rejection; outcome; opportunity mismatch; recovery; trace | Opportunity and interaction contracts; Measurement Handbook evidence separation; Experimental Handbook trace protocol | `sandhu1996`; `ferraiolo2003`; `vanderaalst2016`; `fipa2002`; `taylor1994` | Demonstrates that an exposed, signaled, and believed action can still be incapable and rejected, then records a distinct recovery action. It does not infer intent, honesty, trust, understanding, or real tool access. | | CIS-EX-008 | projection; exposure; signaling; belief; selection; recovery; behavioral evidence; measurement; explanatory gain; predictive gain | Projection, Opportunity, Interaction, Behavioral Evidence, Measurement, and optional Prediction contracts; Experimental and Measurement Handbooks | `gibson1979`; `sandhu1996`; `vanderaalst2016`; `stevens1946`; `cronbach1955`; `yarkoni2017` | Defines a proposed study and explicit freeze gate. It contains no observations, preregistration, validated instrument, causal result, prediction, or transport claim. | ## Alignment requirements Every new interactive figure must identify: 1. the canonical concepts it instantiates; 2. the exact internal definition or protocol it operationalizes; 3. candidate source keys already present in the evidence package; 4. the observable interaction that tests the concept separation; 5. prohibited inferences and empirical claims; 6. executable or browser checks that would falsify the figure's behavior. Source claims must not be strengthened until the evidence register is manually ratified. A visually compelling relationship is not evidence that the relationship is theoretically or empirically valid. ======================================================================== ## FILE: app/examples/README.md (287 lines, 13.6 KiB) ======================================================================== # Identified Examples Every example has a stable `CIS-EX-NNN` identifier. The identifier must appear in the example source, this registry, tests that assert its contract when applicable, and any validation document that cites it. Identifiers are never reused. Material semantic changes require a new example identifier; corrections that restore the documented contract retain the identifier and update its validation history. `manifest.csv` is the machine-readable index. Interactive examples keep an editable HTML fragment under `visualizations/src/` and a generated standalone HTML file under `visualizations/`; both carry the same identifier and theory version. `make test` fails when any registered example, description, editable source, standalone output, or source identifier is missing. ## CIS-EX-001 — Minimal Door Transition **Source:** `door.c` **Run:** `make demo` **Theory version:** 1.0.0 **Implementation status:** executable C example Purpose: demonstrate the smallest complete path through the public API without introducing application architecture. The example declares one `door_open` state cell with bounds `[0, 1]`, one `open` action, one participant, one capability requirement, one role permission, one precondition, one effect, and one preserved projection field. It executes at caller-supplied tick `1` and prints projected state, trace length, and deterministic state hash. Concepts exercised: domain commitments, system state, semantic assignment, participant, agent, capability, permission, enablement, action, state transition, projection, trace, token identity, and Fundamental. Expected behavior: execution commits exactly one `0 → 1` transition, produces one trace event, projects value `1`, and prints hash `8184434590310759885`. Any other state, event count, result, or hash is a conformance failure. Non-claims: the example does not establish interaction recurrence, successful outcome, affordance, discoverability, behavior, strategy, or empirical validity. ## CIS-EX-002 — Door State Conformance Vectors **Source:** `conformance.c` **Run:** `make conformance` **Theory version:** 1.0.0 **Implementation status:** executable C reference generator Purpose: establish a cross-representation identity check for the two-cell door domain shared with CIS-EX-003. The example enumerates `position × locked` in stable order and hashes each state using the production implementation. It is a reference generator, not a second hash implementation. Concepts exercised: system state, representation, scoped invariance, token identity, equivalence, trace-independent snapshot identity, and Fundamental. Expected vectors: | Position | Locked | State hash | |---:|---:|---:| | 0 | 0 | 16981056525137609861 | | 0 | 1 | 14748741118170020452 | | 1 | 0 | 11289045597036932164 | | 1 | 1 | 13521361004004521573 | The vectors are golden assertions in `tests/test_cis.c` and live parity checks in CIS-EX-003. A hash match establishes encoding parity only; it does not prove semantic, behavioral, or interactional equivalence. ## CIS-EX-003 — Interaction Substrate Lab **Editable source:** `visualizations/src/interaction-substrate-lab.html` **Standalone source:** `visualizations/interaction-substrate-lab.html` **Open:** load the file directly in a modern browser **Theory version:** 1.0.0 **Implementation status:** self-contained interactive example Purpose: make the research separations directly experienceable. The lab uses a two-cell door domain (`position`, `locked`), four actions (`open`, `close`, `lock`, `unlock`), and three participants whose roles and capabilities differ. It exposes the complete opportunity profile while actions are selected, accepted, rejected, executed, and assigned an explicit outcome. Controls: - participant changes role and capability conditions; - intended action also declares the reachability target; - outcome after execution keeps an unobserved outcome separate from failure; - search horizon bounds breadth-first reachability; - exposed, signaled, and believed switches vary independent opportunity axes; - attempt records an accepted or rejected selection atomically; - reset creates a fresh local episode. Visible evidence: - current state and projection; - separate conclusions for system executability, projected availability, and belief alignment; - parity against all four CIS-EX-002 C vectors; - twelve independent opportunity and trace predicates, including unknown outcome rather than false success when no outcome was observed; - belief-versus-executable-availability mismatch; - participant-lane event trace with committed, rejected, successful, failed, and unknown outcomes encoded separately. Concepts exercised: domain commitments, state, operational semantics, participant, agent, environment, projection, capability, permission, enablement, reachability, exposure, signaling, believed action, action, transition, opportunity profile, trace, measurement mismatch, reversibility, comparison parity, and Fundamental. Expected behavior: rejected actions never mutate state; unknown outcomes never imply success; exposure never implies signaling or belief; reachability changes with participant authority and horizon; reversibility requires an authorized exact forward/reverse round trip; every reachable door state matches its C hash. Non-claims: the trace is an experiential aid, not behavioral evidence. The lab does not infer affordance, discoverability, uptake, causal recurrence, interaction type, policy, strategy, mechanism, or generalized validity. Validation: browser checks cover successful and rejected transitions, explicit outcomes, dimension independence, C-vector parity, narrow reflow, overflow, and runtime diagnostics. The authoritative findings and boundaries are recorded in `../CONCEPT_VALIDATION.md`. ## CIS-EX-004 — Projection and Invariance Workbench **Editable source:** `visualizations/src/projection-invariance-workbench.html` **Standalone source:** `visualizations/projection-invariance-workbench.html` **Open:** load the standalone file directly in a modern browser **Theory version:** 1.0.0 **Implementation status:** self-contained interactive figure Purpose: make a projection contract inspectable. One declared target is rendered through a fixed operator projection and an adjustable comparison projection. Users can preserve, transform, omit, or introduce fields and observe which typed comparison claims remain licensed. Controls: temperature may be preserved in Celsius, transformed to Fahrenheit, or omitted; alarm state may be preserved or omitted; a summary label may be introduced. The figure reports common comparison space, normalized temperature information, alarm-task invariance, structural equivalence, and a final typed verdict without collapsing them into one score. Concepts exercised: representation, projection, scoped invariance, transformation, omission, introduced structure, correspondence, equivalence, similarity, incomparability, and similarity contract. Expected behavior: an invertible unit transform preserves temperature information but breaks structural equivalence; omitting alarm removes evidence for alarm-task invariance; an introduced summary breaks exact structure; no common observable produces incomparability; partial preservation never reports overall equivalence. Non-claims: matching values do not establish token identity, behavioral or interactional equivalence, observer interpretation, construct validity, or empirical usefulness. ## CIS-EX-005 — Evidence and Inference Ladder **Editable source:** `visualizations/src/evidence-inference-ladder.html` **Standalone source:** `visualizations/evidence-inference-ladder.html` **Open:** load the standalone file directly in a modern browser **Theory version:** 1.0.0 **Implementation status:** self-contained interactive figure Purpose: operationalize the Measurement Handbook's eight evidence levels and the governing rule that a metric is not a construct. A fixed raw event remains constant while users enable the evidential gates required to license stronger statements. Controls: instrument verification, independent coding, preregistered estimator, model calibration, construct validity, causal-alternative tests, and independent scope replication form an ordered chain. Later checks cannot bypass an earlier missing gate. Concepts exercised: raw record, verified observation, coded observation, derived measure, model estimate, construct evidence, mechanism evidence, generalized claim, measurement contract, behavioral evidence, uncertainty boundary, and prohibited interpretation. Expected behavior: the highest defensible statement advances exactly one level for each contiguous satisfied gate; an unchecked earlier gate blocks all later claims; a raw latency never becomes construct, mechanism, or generalized evidence by visual emphasis alone. Non-claims: the example does not validate the fixed record, operationalization, construct, model, mechanism, population, or transport domain. Its purpose is to show the evidence required before those claims could be considered. ## CIS-EX-006 — GUI/CLI Projection Benchmark **Source:** `benchmarks/projection-benchmark.c` **Run:** `make benchmarks` **Theory version:** 1.0.0 **Implementation status:** executable C benchmark Purpose: hold domain state, action semantics, participant authority, and the projected semantic field constant while varying interface signaling. The GUI projection exposes and signals `save`; the CLI projection exposes the same action without signaling it. Concepts exercised: representation, projection, scoped invariance, exposure, signaling, believed availability, opportunity profile, correspondence, and typed comparison. Expected behavior: the projected states are exactly equivalent at similarity `10000/10000`; exposure agrees; signaling differs. The program exits nonzero if any of those assertions fails. Non-claims: semantic projection equivalence does not establish interface, behavioral, interactional, accessibility, usability, or outcome equivalence. ## CIS-EX-007 — Conversational Overclaim Benchmark **Source:** `benchmarks/overclaim-benchmark.c` **Run:** `make benchmarks` **Theory version:** 1.0.0 **Implementation status:** executable C benchmark Purpose: model a conversational assistant that presents an external-send action despite lacking the required capability. The attempted action must be rejected without state mutation. A separate supported action records an explicit limitation and recovery outcome. Concepts exercised: participant, capability, permission, exposure, signaling, belief, selection, rejection, execution, outcome, opportunity mismatch, recovery, and trace. Expected behavior: the unsupported action returns `CIS_ERR_CAPABILITY`, records a rejected trace event, and leaves state unchanged. The explanation action then executes, receives an explicit success outcome, and resolves the belief-versus- availability mismatch. The program exits nonzero on any conflation. Non-claims: the benchmark does not model natural-language understanding, honesty, intention, trust, user interpretation, or real external tool access. ## CIS-EX-008 — Projection Signaling Study Protocol **Source:** `studies/CIS-EX-008_projection-signaling-study.md` **Use:** protocol review only **Theory version:** 1.0.0 **Implementation status:** proposed worked study; not preregistered or executed Purpose: translate the first decisive empirical question into a bounded, counterbalanced design while exposing every unresolved decision that must be closed before participant collection. Inputs: two governed projections over one target and operation set; frozen contract instances; reviewed instruments, coding rules, governance, consent, sample-size rationale, counterbalancing, and analysis plan. Associated artifacts: `studies/CIS-EX-008/contracts/` contains ten complete draft 0.2.0 instances covering both projections, opportunity, interaction, behavioral evidence, and five separately scoped measurements. They are structurally checked but deliberately remain draft and unauthorized for collection. `studies/CIS-EX-008/data/` adds identified positive and negative synthetic dataset fixtures covering the record-to-measure lineage without fabricating empirical evidence. Concepts exercised: projection, exposure, signaling, believed availability, selection, execution, recovery, formal and behavioral trace separation, measurement, uncertainty, carryover, explanatory gain, and predictive gain. Expected behavior: reviewers can trace each proposed variable from instrument record through coding and measurement to a bounded claim, and the freeze gate prevents collection while identifiers, governance, instruments, or review are unresolved. Dependency-free tests accept every complete draft instance and the synthetic study fixture, then reject the intentionally incomplete study fixture. Non-claims: this protocol contains no participants, observations, effect size, validated instrument, preregistration, causal result, predictive result, or generalization. Research alignment for CIS-EX-003 through CIS-EX-008 is maintained in `PAPER_ALIGNMENT.md`. ## Visual quality contract Interactive figures are research interfaces, not decorative supplements. Each must make one primary relationship dominant, group controls by analytical role, show false and unknown states without hiding them, use color only with a text or shape cue, retain native keyboard controls, fit without horizontal overflow at 320 pixels, avoid large empty plot regions, and expose the example identifier and theory version. Visual emphasis must never imply equivalence, causality, validity, success, or generalization unless the corresponding computational or evidential gate is satisfied. ======================================================================== ## FILE: app/examples/benchmarks/README.md (18 lines, 1.0 KiB) ======================================================================== # FCI Benchmark Suite 0.1.0 Benchmarks are identified examples with executable assertions. They remain deterministic reference tests, not empirical studies. | ID | Source | Contract set | Expected output | |---|---|---|---| | CIS-EX-006 | `projection-benchmark.c` | Projection; Opportunity; Comparison | `PASS: state projection invariant; signaling intentionally differs` | | CIS-EX-007 | `overclaim-benchmark.c` | Opportunity; Interaction; Behavioral Evidence boundary; Measurement boundary | `PASS: unsupported claim rejected; limitation recovery recorded` | `make benchmarks` builds and executes both programs; `make test` treats any nonzero exit as failure. Exact purposes, exercised concepts, research claims, non-claims, and validation definitions are controlled by `../README.md` and `../PAPER_ALIGNMENT.md`. Path cost, discoverability, trust, novice/expert differences, auditability, accessibility, concurrency, and real external-tool behavior require empirical or richer formal layers and are not fabricated by these deterministic fixtures. ======================================================================== ## FILE: app/examples/benchmarks/overclaim-benchmark.c (74 lines, 2.9 KiB) ======================================================================== #include "cis.h" #include /* * CIS-EX-007 — Conversational Overclaim Benchmark * * Models an assistant that exposes and signals an action it cannot perform. * Belief, presentation, selection, rejection, and recovery remain separate. */ int main(void) { CisDomain domain; CisAction send; CisAction explain; CisState initial = {{0}, 1}; CisSystem system; CisProjection projection; CisOpportunity before; CisOpportunity after; CisPredicate target; uint8_t explained_index; uint8_t send_index; uint8_t explain_index; uint8_t assistant_index; CisResult send_result; cis_domain_init(&domain); if (cis_domain_add_variable(&domain, "limitation_explained", 0, 1, &explained_index) != CIS_OK) return 1; cis_action_init(&send, "send_external_message"); send.required_capabilities = 2u; send.permitted_roles = 1u; cis_action_init(&explain, "explain_limitation"); explain.required_capabilities = 1u; explain.permitted_roles = 1u; if (cis_action_add_effect(&explain, (CisEffect){explained_index, CIS_EFFECT_SET, 1}) != CIS_OK || cis_domain_add_action(&domain, &send, &send_index) != CIS_OK || cis_domain_add_action(&domain, &explain, &explain_index) != CIS_OK || cis_system_init(&system, &domain, &initial) != CIS_OK || cis_system_add_participant(&system, "assistant", 0u, 1u, &assistant_index) != CIS_OK) return 1; cis_projection_init(&projection); projection.exposed_actions = UINT32_C(1) << send_index; projection.signaled_actions = UINT32_C(1) << send_index; target = (CisPredicate){explained_index, CIS_PRED_EQ, 1}; if (cis_opportunity(&system, &projection, assistant_index, send_index, 1u, 9000u, 1, 1000u, &target, 1u, &before) != CIS_OK) { return 1; } send_result = cis_execute(&system, assistant_index, send_index, 1u); if (send_result != CIS_ERR_CAPABILITY || system.state.values[0] != 0 || system.trace_count != 1u || system.trace[0].status != CIS_EVENT_REJECTED || before.capable || !before.exposed || !before.signaled || !before.believed_available || cis_measure_opportunity_mismatch(&before) == 0u) return 1; if (cis_execute(&system, assistant_index, explain_index, 2u) != CIS_OK || cis_record_outcome(&system, 1u, CIS_OUTCOME_SUCCESS) != CIS_OK || system.state.values[0] != 1 || system.trace_count != 2u || cis_opportunity(&system, &projection, assistant_index, send_index, 0u, 10000u, 0, 0u, &target, 1u, &after) != CIS_OK || after.believed_available || after.capable || cis_measure_opportunity_mismatch(&after) != 0u) return 1; puts("PASS: unsupported claim rejected; limitation recovery recorded"); return 0; } ======================================================================== ## FILE: app/examples/benchmarks/projection-benchmark.c (72 lines, 2.8 KiB) ======================================================================== #include "cis.h" #include /* * CIS-EX-006 — GUI/CLI Projection Benchmark * * Holds domain state and semantics constant while two interfaces vary action * exposure and signaling. This tests scoped projection invariance without * treating interface similarity as interaction equivalence. */ int main(void) { CisDomain domain; CisAction save; CisState initial = {{7}, 1}; CisSystem system; CisProjection gui; CisProjection cli; CisProjectedState gui_state; CisProjectedState cli_state; CisOpportunity gui_opportunity; CisOpportunity cli_opportunity; CisPredicate target; CisComparison comparison; uint8_t value_index; uint8_t save_index; uint8_t participant_index; cis_domain_init(&domain); if (cis_domain_add_variable(&domain, "document_value", 0, 9, &value_index) != CIS_OK) return 1; cis_action_init(&save, "save"); save.required_capabilities = 1u; save.permitted_roles = 1u; if (cis_action_add_precondition(&save, (CisPredicate){value_index, CIS_PRED_GE, 0}) != CIS_OK || cis_domain_add_action(&domain, &save, &save_index) != CIS_OK || cis_system_init(&system, &domain, &initial) != CIS_OK || cis_system_add_participant(&system, "editor", 0u, 1u, &participant_index) != CIS_OK) return 1; cis_projection_init(&gui); gui.exposed_actions = UINT32_C(1) << save_index; gui.signaled_actions = UINT32_C(1) << save_index; cis_projection_init(&cli); cli.exposed_actions = UINT32_C(1) << save_index; if (cis_projection_add_field(&gui, "document_value", value_index, 1, 0, CIS_FIELD_PRESERVED) != CIS_OK || cis_projection_add_field(&cli, "document_value", value_index, 1, 0, CIS_FIELD_PRESERVED) != CIS_OK || cis_project(&gui, &system.state, &gui_state) != CIS_OK || cis_project(&cli, &system.state, &cli_state) != CIS_OK) return 1; target = (CisPredicate){value_index, CIS_PRED_EQ, 7}; if (cis_opportunity(&system, &gui, participant_index, save_index, 1u, 10000u, 0, 0u, &target, 0u, &gui_opportunity) != CIS_OK || cis_opportunity(&system, &cli, participant_index, save_index, 1u, 10000u, 0, 0u, &target, 0u, &cli_opportunity) != CIS_OK) return 1; comparison = cis_compare_projections(&gui_state, &cli_state); if (!comparison.comparable || !comparison.equivalent || comparison.similarity_permyriad != 10000u || !gui_opportunity.exposed || !cli_opportunity.exposed || !gui_opportunity.signaled || cli_opportunity.signaled) return 1; puts("PASS: state projection invariant; signaling intentionally differs"); return 0; } ======================================================================== ## FILE: app/examples/conformance.c (30 lines, 0.8 KiB) ======================================================================== #include "cis.h" #include #include /* * CIS-EX-002 — Door State Conformance Vectors * * Enumerates the four states shared by the C fixture and interactive example, * then emits their canonical integer-encoding hashes. The vectors identify * representation drift between the freestanding substrate and experiential * model. See examples/README.md for the complete contract. */ int main(void) { CisState state = {{0, 0}, 2}; uint8_t position; uint8_t locked; puts("position\tlocked\thash"); for (position = 0u; position <= 1u; ++position) { for (locked = 0u; locked <= 1u; ++locked) { state.values[0] = position; state.values[1] = locked; printf("%u\t%u\t%" PRIu64 "\n", position, locked, cis_state_hash(&state)); } } return 0; } ======================================================================== ## FILE: app/examples/door.c (59 lines, 2.0 KiB) ======================================================================== #include "cis.h" #include #include /* * CIS-EX-001 — Minimal Door Transition * * Smallest complete use of the substrate: declare one bounded state cell, * assign operational semantics to one action, authorize one participant, * commit one transition, project the resulting state, and print its stable * hash. See examples/README.md for the concept and validation contract. */ int main(void) { CisDomain domain; CisAction open; CisState initial = {{0}, 1}; CisSystem system; CisProjection projection; CisProjectedState view; uint8_t position; uint8_t open_index; uint8_t person; CisResult result; cis_domain_init(&domain); result = cis_domain_add_variable(&domain, "door_open", 0, 1, &position); if (result != CIS_OK) return 1; cis_action_init(&open, "open"); open.required_capabilities = 1u; open.permitted_roles = 1u; if (cis_action_add_precondition(&open, (CisPredicate){position, CIS_PRED_EQ, 0}) != CIS_OK || cis_action_add_effect(&open, (CisEffect){position, CIS_EFFECT_SET, 1}) != CIS_OK || cis_domain_add_action(&domain, &open, &open_index) != CIS_OK || cis_system_init(&system, &domain, &initial) != CIS_OK || cis_system_add_participant(&system, "person", 0, 1u, &person) != CIS_OK) { return 1; } cis_projection_init(&projection); projection.exposed_actions = UINT32_C(1) << open_index; projection.signaled_actions = UINT32_C(1) << open_index; if (cis_projection_add_field(&projection, "door_open", position, 1, 0, CIS_FIELD_PRESERVED) != CIS_OK || cis_execute(&system, person, open_index, 1u) != CIS_OK || cis_project(&projection, &system.state, &view) != CIS_OK) { return 1; } printf("state=%" PRId64 " events=%u hash=%" PRIu64 "\n", view.values[0], (unsigned)system.trace_count, cis_state_hash(&system.state)); return 0; } ======================================================================== ## FILE: app/examples/manifest.csv (9 lines, 1.6 KiB) ======================================================================== example_id,title,type,source,theory_version,run_or_open,validation_definition CIS-EX-001,Minimal Door Transition,C,examples/door.c,1.0.0,make demo,examples/README.md#cis-ex-001--minimal-door-transition CIS-EX-002,Door State Conformance Vectors,C,examples/conformance.c,1.0.0,make conformance,examples/README.md#cis-ex-002--door-state-conformance-vectors CIS-EX-003,Interaction Substrate Lab,HTML,examples/visualizations/src/interaction-substrate-lab.html,1.0.0,open examples/visualizations/interaction-substrate-lab.html in browser,examples/README.md#cis-ex-003--interaction-substrate-lab CIS-EX-004,Projection and Invariance Workbench,HTML,examples/visualizations/src/projection-invariance-workbench.html,1.0.0,open examples/visualizations/projection-invariance-workbench.html in browser,examples/README.md#cis-ex-004--projection-and-invariance-workbench CIS-EX-005,Evidence and Inference Ladder,HTML,examples/visualizations/src/evidence-inference-ladder.html,1.0.0,open examples/visualizations/evidence-inference-ladder.html in browser,examples/README.md#cis-ex-005--evidence-and-inference-ladder CIS-EX-006,GUI/CLI Projection Benchmark,C,examples/benchmarks/projection-benchmark.c,1.0.0,make benchmarks,examples/README.md#cis-ex-006--guicli-projection-benchmark CIS-EX-007,Conversational Overclaim Benchmark,C,examples/benchmarks/overclaim-benchmark.c,1.0.0,make benchmarks,examples/README.md#cis-ex-007--conversational-overclaim-benchmark CIS-EX-008,Projection Signaling Study Protocol,STUDY_PROTOCOL,examples/studies/CIS-EX-008_projection-signaling-study.md,1.0.0,read protocol,examples/README.md#cis-ex-008--projection-signaling-study-protocol ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/README.md (28 lines, 1.4 KiB) ======================================================================== # CIS-EX-008 Draft Contract Package These ten instances operationalize the proposed projection-signaling study. They are identified components of CIS-EX-008, not independent examples. | Claim boundary | Instance | |---|---| | signaled condition | `projection-signaled.json` | | exposed but unsignaled condition | `projection-unsignaled.json` | | independent opportunity predicates | `opportunity.json` | | reciprocal episode boundary | `interaction.json` | | record, coding, attribution, and claim lineage | `behavioral-evidence.json` | | unprompted discovery | `measurement-discovery.json` | | rejected unavailable attempts | `measurement-invalid-attempt.json` | | recovery duration | `measurement-recovery.json` | | explicit completion | `measurement-completion.json` | | participant-reported believed availability | `measurement-belief.json` | Every instance is draft 0.2.0, aligned to theory 1.0.0, uses the CIS-EX-008 identity prefix, retains unratified concept identifiers as null, and prohibits interpretations stronger than its evidence. `tests/test_schemas.c` parses every file without external libraries and verifies the common and contract-specific required-field inventory. This is structural validation only. Full JSON Schema evaluation, cross-reference resolution, instrument review, semantic compatibility, canonical-ID ratification, governance approval, and preregistration remain required before a contract may be frozen or used for participant collection. ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/behavioral-evidence.json (55 lines, 4.0 KiB) ======================================================================== { "contract_id": "CIS-EX-008-BEHAVIORAL-EVIDENCE", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Behavioral evidence", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery and recovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": [ "Instrument events do not directly reveal awareness, understanding, intention, trust, or strategy." ], "raw_source_refs": ["CIS-EX-008-INSTRUMENT-EVENT-LOG", "CIS-EX-008-BELIEF-INSTRUMENT"], "instrument_refs": ["CIS-EX-008-INSTRUMENT-EVENT-LOG", "CIS-EX-008-BELIEF-INSTRUMENT"], "observation_model": "Versioned host instrumentation records projection, participant input, system result, state transition, feedback, and monotonic time; participant reports are separate records.", "detection_rules": ["Accept only records whose payload schema, instrument version, episode identity, and monotonic time resolve.", "Retain duplicate, late, and malformed records with an explicit invalid status."], "event_coding_rules": ["Code selection from a resolved participant input record.", "Code execution only from a committed transition.", "Code success only from a verified terminal state and frozen completion predicate."], "segmentation_rules": [ "Start an episode at the first valid projection.ready event for the assigned condition.", "End at the first valid task.complete, task.abandon, invalidity, or timeout event.", "Retain late and duplicate records with invalid status rather than silently deleting them." ], "attribution_rules": [ "Attribute an input only when its participant, episode, projection, and instrument identifiers resolve.", "Code execution only from a committed system transition record.", "Code success only when the explicit completion criterion resolves true." ], "ordering_rule": "Order by monotonic instrument time, then frozen source sequence; unresolved ties remain unknown for order-dependent measures.", "missingness_rules": { "missing_required_record": "mark the affected event or measure missing_unknown", "invalid_record": "retain for audit and exclude only under the frozen rule", "absence_of_event": "encode observed absence only when the full observation window is valid" }, "alternative_explanations": ["prior familiarity", "order and carryover", "latency difference", "uncontrolled host signifier", "instruction or training difference", "device or accessibility mismatch"], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-EVIDENCE", "version": "0.1.0" }, "falsifying_evidence": ["Independent recoding does not reproduce primary event labels within the frozen tolerance.", "Required event identity or ordering cannot be resolved.", "Condition assignment and recorded projection version disagree."], "claim_limits": ["Non-selection cannot be coded as non-awareness.", "A trace cannot be labeled a strategy.", "Condition differences do not identify a universal perceptual mechanism."], "review_requirements": { "technical": "verify identity resolution, ordering, replay, and condition assignment", "human": "independent review of ambiguous coding and primary-claim boundary before release" }, "evidence_lineage_rule": "Every coded event names its source records and rule version; every derived measure names its coded events, contract, estimator, and software version.", "provenance_requirements": { "raw": "append-only source identifier, instrument version, recorded time, and payload schema", "coded": "coder or deterministic rule version, input record references, adjudication status, and transformation time", "derived": "contract, estimator, code, and environment versions" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/interaction.json (65 lines, 4.4 KiB) ======================================================================== { "contract_id": "CIS-EX-008-INTERACTION", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Interaction episode", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery and recovery task", "projection": "one frozen CIS-EX-008 condition", "context": "controlled technical pilot" }, "prohibited_interpretations": [ "An isolated participant input or system output does not by itself establish a strict interaction episode." ], "participant_refs": ["CIS-EX-008-PARTICIPANT", "CIS-EX-008-TARGET-SYSTEM"], "environment_refs": ["CIS-EX-008-ENVIRONMENT-CONTROLLED"], "boundary": "Begins when the frozen projection becomes actionable; ends at completion, abandonment, invalid instrumentation, or the preregistered timeout.", "timescale": "condition-level episode using monotonic instrument time", "initiation_conditions": ["The assigned projection, target, instrument, and authority versions resolve and projection.ready is recorded."], "initial_state_ref": "CIS-EX-008-STATE-INITIAL", "coupling_relations": [ { "source_ref": "CIS-EX-008-PARTICIPANT", "target_ref": "CIS-EX-008-TARGET-SYSTEM", "pathway": "selection through an exposed operation path", "possible_consequence": "target transition, rejection, or unchanged state" }, { "source_ref": "CIS-EX-008-TARGET-SYSTEM", "target_ref": "CIS-EX-008-PARTICIPANT", "pathway": "versioned projection feedback", "possible_consequence": "later selection, recovery, completion, or abandonment" } ], "perturbation_conditions": ["A valid participant selection reaches the target system through the exposed operation path."], "uptake_conditions": ["The target system resolves the selection and emits a typed rejection or committed transition with feedback."], "preconditions": [ "Assigned projection and target versions loaded.", "Instrument clock and event capture pass technical verification.", "Participant has completed standardized training and the active condition has not been exposed previously in the measured block." ], "postconditions": ["Termination type, last verified state, and unresolved evidence status are recorded."], "event_types": ["projection.ready", "belief.report", "action.select", "action.reject", "transition.commit", "feedback.present", "recovery.select", "task.complete", "task.abandon"], "transition_semantics_ref": { "id": "CIS-EX-008-TRANSITION-SEMANTICS", "version": "0.1.0" }, "protocol": "Present condition, collect pre-outcome belief report, permit action sequence, present frozen feedback after each attempt, and terminate under the declared completion, abandonment, invalidity, or timeout rule.", "invariants": ["Target semantics and operation vocabulary remain constant across conditions.", "Rejected actions do not mutate target state."], "evidence_requirements": { "coupling": "time-linked participant action and system feedback records", "recurrence": "at least one feedback event precedes a later participant selection or explicit termination response" }, "failure_conditions": ["Required event capture is missing or non-monotonic.", "Condition versions change inside an episode.", "A rejected action mutates target state."], "recovery_conditions": ["The recovery operation restores the declared recoverable state.", "A participant may abandon without being coded as recovered."], "completion_conditions": ["The target state and frozen explicit success criterion are both satisfied."], "episode_identity_rule": "Use the assigned participant-condition-block identity; duplicate starts are retained and invalidate the episode unless the frozen adjudication rule resolves one canonical start.", "provenance_requirements": { "raw": "participant, episode, projection, instrument, source, and monotonic capture identity", "derived": "input record references plus contract, coding-rule, and software versions" }, "uncertainty_assumptions": ["Clock ordering is resolvable within the declared resolution.", "Attribution is unknown when participant, episode, or projection identity does not resolve.", "Missing recurrence evidence does not establish absence of interaction."] } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/measurement-belief.json (49 lines, 3.3 KiB) ======================================================================== { "contract_id": "CIS-EX-008-MEASUREMENT-BELIEF", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Believed availability", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending cognitive interviewing and measurement review", "task": "bounded target-operation discovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": ["The report is not direct access to awareness, confidence, expected consequence, trust, or actual availability."], "measurand": "participant response to the frozen pre-outcome question of whether the target action is currently available", "unit": null, "level_of_analysis": "participant-condition report", "observation_model": "A time-linked participant response is recorded before target outcome disclosure and preserved separately from system availability predicates.", "instrument_ref": { "id": "CIS-EX-008-BELIEF-INSTRUMENT", "version": "0.1.0" }, "operationalization": "Map the frozen yes, no, and unsure response options to distinct categories; never infer a missing report from behavior.", "coding_rules": ["Preserve unsure as a category.", "Record nonresponse as missing rather than no.", "Exclude reports administered after target outcome disclosure from the primary measure."], "estimator": "preregistered multinomial or explicitly dichotomized condition contrast with participant repeated structure", "scale_type": "nominal", "permissible_transformations": ["preregistered category relabeling", "declared binary collapse with unsure and missing treatment specified"], "permissible_comparisons": ["condition contrast after instrument invariance and administration checks"], "permitted_interpretations": ["The value is the participant's recorded response to the frozen availability question before target outcome disclosure."], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-BELIEF", "version": "0.1.0" }, "uncertainty_budget": { "wording": "interpretation is bounded to populations and modalities covered by cognitive review", "administration_time": "late administration invalidates the primary measure", "nonresponse": "represented as missing_unknown and never inferred from behavior" }, "reliability_evidence_requirements": ["administration timing and response capture verified", "test-retest interpretation declared if assessed"], "validity_evidence_requirements": ["cognitive interviews support the intended reading", "response behavior is evaluated separately from actual availability"], "comparison_scope": { "population": "population for which the instrument wording and modality were reviewed", "task": "frozen target-operation discovery task", "projection": "frozen CIS-EX-008 condition versions", "context": "reviewed instrument modality, language, device, and administration timing" }, "missingness_rules": { "nonresponse": "mark missing_unknown", "unsure": "retain as observed category", "late_administration": "mark invalid for the primary estimand" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/measurement-completion.json (49 lines, 3.1 KiB) ======================================================================== { "contract_id": "CIS-EX-008-MEASUREMENT-COMPLETION", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Task completion", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": ["Equal completion does not establish equal discovery, understanding, effort, accessibility, or interaction equivalence."], "measurand": "whether the terminal target state and explicit success criterion are satisfied before abandonment or timeout", "unit": null, "level_of_analysis": "participant-condition episode", "observation_model": "Replay-verified terminal state and the frozen completion predicate determine completion.", "instrument_ref": { "id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "version": "0.1.0" }, "operationalization": "One when both terminal target state and explicit criterion resolve true; zero after validly observed timeout or abandonment without completion; missing or invalid when terminal evidence cannot be resolved.", "coding_rules": ["Execution alone is insufficient.", "Unknown outcome remains unknown rather than failure unless the frozen termination rule licenses zero."], "estimator": "preregistered condition contrast in completion probability with participant repeated structure", "scale_type": "binary", "permissible_transformations": ["logical complement with relabeled estimand"], "permissible_comparisons": ["condition contrast with identical completion criterion and timeout"], "permitted_interpretations": ["The episode satisfied the frozen terminal state and explicit success criterion within a validly observed termination window."], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-COMPLETION", "version": "0.1.0" }, "uncertainty_budget": { "terminal_state": "unresolved replay produces missing_unknown or invalid, never inferred failure", "criterion": "criterion version must resolve before classification", "termination": "timeout or abandonment is zero only under the frozen rule" }, "reliability_evidence_requirements": ["independent replay reproduces terminal state and criterion evaluation"], "validity_evidence_requirements": ["completion criterion represents the frozen task target without condition-specific advantage"], "comparison_scope": { "population": "reviewed and adequately supported study population", "task": "frozen target-operation discovery task", "projection": "frozen CIS-EX-008 condition versions", "context": "reviewed devices, instructions, training, and setting" }, "missingness_rules": { "invalid_terminal_state": "mark invalid", "valid_timeout_or_abandonment": "record zero only when the frozen rule defines noncompletion", "unresolved_outcome": "mark missing_unknown" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/measurement-discovery.json (49 lines, 3.2 KiB) ======================================================================== { "contract_id": "CIS-EX-008-MEASUREMENT-DISCOVERY", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Unprompted discovery event", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": ["Selection is not proof of awareness before selection, understanding, or general discoverability."], "measurand": "whether the first valid target-action selection preceded any prompt or target-operation disclosure", "unit": null, "level_of_analysis": "participant-condition episode", "observation_model": "Time-linked prompt, disclosure, and valid selection events are observed by the frozen instrument and coded under the Behavioral Evidence Contract.", "instrument_ref": { "id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "version": "0.1.0" }, "operationalization": "One when a valid target selection occurs before every prompt or disclosure event in the episode; zero when a prompt or disclosure occurs first; missing when ordering or required capture is unresolved.", "coding_rules": ["Use monotonic event order after identity resolution.", "Do not convert unresolved ordering, abandonment before observability, or invalid capture to zero."], "estimator": "preregistered condition contrast in episode-level probability with participant repeated structure", "scale_type": "binary", "permissible_transformations": ["logical complement with relabeled estimand"], "permissible_comparisons": ["signaled versus unsignaled condition inside the reviewed scope"], "permitted_interpretations": ["Within the frozen observation window, the recorded target selection preceded every detected prompt or target-operation disclosure."], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-DISCOVERY", "version": "0.1.0" }, "uncertainty_budget": { "event_order": "bounded by verified monotonic-clock resolution", "prompt_detection": "unresolved prompts invalidate the primary episode measure", "instrument_capture": "missing required records produce missing_unknown" }, "reliability_evidence_requirements": ["independent reproduction of event ordering and prompt classification"], "validity_evidence_requirements": ["audit that prompts and uncontrolled target signifiers are detected", "manipulation check that the declared signifier differs between conditions"], "comparison_scope": { "population": "reviewed and adequately supported study population", "task": "frozen target-operation discovery task", "projection": "frozen CIS-EX-008 condition versions", "context": "reviewed devices, instructions, training, and setting" }, "missingness_rules": { "invalid_capture": "mark invalid and retain audit count", "unresolved_order": "mark missing_unknown", "abandonment": "report separately; do not recode automatically" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/measurement-invalid-attempt.json (49 lines, 3.2 KiB) ======================================================================== { "contract_id": "CIS-EX-008-MEASUREMENT-INVALID-ATTEMPT", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Attempted unavailable action", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery and recovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": ["A rejected attempt does not establish misunderstanding, carelessness, or participant deficit."], "measurand": "count of valid selections rejected for capability, permission, or enablement before episode termination", "unit": "attempts", "level_of_analysis": "participant-condition episode", "observation_model": "Each resolved selection is linked to the pre-action opportunity profile and typed execution result.", "instrument_ref": { "id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "version": "0.1.0" }, "operationalization": "Count selections with a resolved rejection result of capability absent, permission denied, or precondition unsatisfied; exclude instrument-invalid selections and report them separately.", "coding_rules": ["Resolve the pre-action state and authority version before classifying.", "Do not treat a hidden or unsignaled executable action as system-unavailable."], "estimator": "preregistered condition contrast for episode counts with exposure time or opportunity count declared", "scale_type": "count", "permissible_transformations": ["rate per declared opportunity count when preregistered"], "permissible_comparisons": ["condition contrast with identical target semantics and authority"], "permitted_interpretations": ["The count reports resolved selections rejected for one of the frozen system-availability predicates during a valid observation window."], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-INVALID-ATTEMPT", "version": "0.1.0" }, "uncertainty_budget": { "state_resolution": "unresolved pre-action state invalidates the affected classification", "authority_resolution": "unresolved authority invalidates the affected classification", "exposure": "censored windows retain observed counts and explicit censoring status" }, "reliability_evidence_requirements": ["replay reproduces state, authority, and typed rejection"], "validity_evidence_requirements": ["rejection types are distinguishable from transport and instrumentation failures"], "comparison_scope": { "population": "reviewed and adequately supported study population", "task": "frozen target-operation discovery and recovery task", "projection": "frozen CIS-EX-008 condition versions", "context": "reviewed devices, instructions, training, and setting" }, "missingness_rules": { "unresolved_state_or_authority": "mark invalid", "no_attempt": "record observed zero only when the complete episode was validly observed", "abandonment": "retain observed count and mark exposure as censored" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/measurement-recovery.json (49 lines, 3.2 KiB) ======================================================================== { "contract_id": "CIS-EX-008-MEASUREMENT-RECOVERY", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Recovery duration", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery and recovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": ["Recovery duration is not resilience, confidence, expertise, or strategy."], "measurand": "elapsed monotonic instrument time from a valid failed or rejected attempt to the first verified return to the declared recoverable state", "unit": "milliseconds", "level_of_analysis": "recovery interval nested within participant-condition episode", "observation_model": "Typed attempt results and replay-verified state records delimit a recovery interval.", "instrument_ref": { "id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "version": "0.1.0" }, "operationalization": "Subtract failure-event time from the first later state record satisfying the frozen recovery predicate; censor at abandonment or timeout; mark invalid when replay or timing diverges.", "coding_rules": ["Use the first qualifying state after the indexed failure.", "Keep censored, invalid, missing, and observed-zero intervals distinct."], "estimator": "preregistered time-to-recovery model with participant repeated structure and declared censoring", "scale_type": "duration", "permissible_transformations": ["positive unit conversion", "preregistered monotonic transformation with estimand restated"], "permissible_comparisons": ["condition contrast under equivalent clock, timeout, failure, and recovery definitions"], "permitted_interpretations": ["The duration reports instrument time from a qualifying failure to the first replay-verified recoverable state under the frozen rule."], "uncertainty_model_ref": { "id": "CIS-EX-008-UNCERTAINTY-RECOVERY", "version": "0.1.0" }, "uncertainty_budget": { "clock": "bounded by verified resolution and synchronization error", "state_replay": "divergence marks the interval invalid", "censoring": "timeout and abandonment are represented explicitly rather than imputed" }, "reliability_evidence_requirements": ["replay reproduces failure and recovery states", "clock resolution and synchronization verified"], "validity_evidence_requirements": ["recovery predicate is task-relevant and frozen before observation", "censoring mechanisms are reported"], "comparison_scope": { "population": "reviewed and adequately supported study population", "task": "frozen target-operation discovery and recovery task", "projection": "frozen CIS-EX-008 condition versions", "context": "reviewed devices, instructions, training, and setting" }, "missingness_rules": { "timeout_or_abandonment": "right-censor rather than encode zero", "clock_or_replay_failure": "mark invalid", "no_qualifying_failure": "mark not_applicable" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/opportunity.json (56 lines, 3.2 KiB) ======================================================================== { "contract_id": "CIS-EX-008-OPPORTUNITY", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Opportunity profile", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery task", "projection": "CIS-EX-008 signaled and unsignaled conditions", "context": "controlled technical pilot" }, "prohibited_interpretations": [ "No single opportunity predicate implies another, and non-selection does not imply non-awareness." ], "system_ref": "CIS-EX-008-TARGET", "participant_ref": "CIS-EX-008-PARTICIPANT", "action_ref": "CIS-EX-008-ACTION-TARGET", "action_vocabulary_ref": { "id": "CIS-EX-008-ACTION-VOCABULARY", "version": "0.1.0" }, "projection_ref": "CIS-EX-008-PROJECTION-CONDITION", "task_ref": "CIS-EX-008-TASK-DISCOVERY", "authority_ref": "CIS-EX-008-AUTHORITY-MAP", "state_ref": "CIS-EX-008-STATE-AT-EVENT", "time_basis": "monotonic instrument time relative to condition start", "relation_definitions": { "domain_valid": "The target action exists in the frozen target operation vocabulary.", "capable": "The participant and assigned apparatus satisfy the target action capability requirements.", "permitted": "The frozen authority map permits the participant role to invoke the target action.", "enabled": "The recorded pre-action state satisfies every target action precondition.", "reachable": "A permitted target state is reachable within the preregistered action horizon under frozen semantics.", "exposed": "The active projection contains an executable path to the target action.", "signaled": "The active projection contains the audited target-operation signifier.", "believed_available": "The participant reports availability through the frozen instrument before outcome disclosure.", "selected": "The instrument records a target action selection event.", "executed": "The system records a committed target transition.", "successful": "A committed transition satisfies the frozen task completion criterion.", "reversible": "The frozen recovery operation restores the exact preregistered state fields under the participant authority." }, "expected_consequence_definition": "The target operation is expected to commit the frozen target transition and present the declared feedback without changing unrelated state.", "recovery_definition": "The recovery operation must restore every preregistered recoverable state field and emit a verifiable transition record.", "evidence_requirements": { "system_relations": "frozen target, authority, state, and execution records", "projection_relations": "versioned projection audit", "belief_relation": "time-linked participant report", "trace_relations": "verified and coded instrument events" }, "uncertainty_requirements": { "timing": "record clock resolution and synchronization error", "coding": "retain unknown when evidence cannot distinguish states", "belief": "record response scale, missingness, and administration time" } } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/projection-signaled.json (45 lines, 2.2 KiB) ======================================================================== { "contract_id": "CIS-EX-008-PROJECTION-SIGNALED", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Projection", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery task", "projection": "signaled action condition", "context": "controlled technical pilot" }, "prohibited_interpretations": [ "Exposure or signaling does not establish perception, understanding, usability, or accessibility." ], "target_ref": { "id": "CIS-EX-008-TARGET", "version": "0.1.0" }, "target_host": "CIS-EX-008-HOST-CONTROLLED", "modality": ["visual", "pointer", "keyboard"], "mapping_rule": "Preserve target state and operation semantics; expose the target operation and render one declared signifier adjacent to its control.", "interpretation_assumptions": [ "The signifier label is understandable only within the reviewed participant and task scope." ], "preserved_properties": ["target state", "operation identity", "transition semantics", "feedback latency bound"], "transformed_properties": ["host-specific control geometry"], "omitted_properties": ["implementation internals"], "introduced_properties": ["target-operation signifier"], "exposed_operations": ["target operation", "recovery operation"], "signifiers": ["adjacent target-operation text label"], "feedback_channels": ["visible state transition", "typed execution result"], "observer_class": "reviewed study participants after standardized training", "intended_use": "test the effect of declared signaling while holding target semantics and exposed operations constant", "tolerances": [ { "property": "feedback latency", "maximum_difference_ms": 10 } ], "uncertainty_refs": ["CIS-EX-008-UNCERTAINTY-INSTRUMENT"], "failure_conditions": [ "Target or recovery operation differs between conditions.", "Measured feedback latency exceeds the preregistered equivalence bound.", "The target signifier is absent or appears in the unsignaled condition." ] } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/contracts/projection-unsignaled.json (45 lines, 2.3 KiB) ======================================================================== { "contract_id": "CIS-EX-008-PROJECTION-UNSIGNALED", "schema_version": "0.2.0", "contract_version": "0.2.0", "theory_version": "1.0.0", "status": "draft", "authority": "CIS-EX-008 proposed protocol; not authorized for collection", "construct_refs": [ { "label": "Projection", "identifier_status": "unratified", "canonical_id": null } ], "scope": { "population": "population pending methods and accessibility review", "task": "bounded target-operation discovery task", "projection": "exposed but unsignaled action condition", "context": "controlled technical pilot" }, "prohibited_interpretations": [ "Absence of the declared signifier does not establish that a participant cannot perceive or discover the operation." ], "target_ref": { "id": "CIS-EX-008-TARGET", "version": "0.1.0" }, "target_host": "CIS-EX-008-HOST-CONTROLLED", "modality": ["visual", "pointer", "keyboard"], "mapping_rule": "Preserve target state and operation semantics; expose the target operation through the same executable control path while omitting the declared target-operation signifier.", "interpretation_assumptions": [ "Other host conventions may still function as signals and must be audited before freezing." ], "preserved_properties": ["target state", "operation identity", "transition semantics", "feedback latency bound"], "transformed_properties": ["host-specific control geometry"], "omitted_properties": ["target-operation signifier", "implementation internals"], "introduced_properties": [], "exposed_operations": ["target operation", "recovery operation"], "signifiers": [], "feedback_channels": ["visible state transition", "typed execution result"], "observer_class": "reviewed study participants after standardized training", "intended_use": "test the effect of removing one declared signifier while preserving target semantics and exposed operations", "tolerances": [ { "property": "feedback latency", "maximum_difference_ms": 10 } ], "uncertainty_refs": ["CIS-EX-008-UNCERTAINTY-INSTRUMENT"], "failure_conditions": [ "Target or recovery operation differs between conditions.", "Measured feedback latency exceeds the preregistered equivalence bound.", "The audited target signifier remains present in this condition." ] } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/data/README.md (16 lines, 0.9 KiB) ======================================================================== # CIS-EX-008 Dataset Fixtures `valid-synthetic-study.json` is an invented, deterministic lineage fixture. It contains no person, observation, effect, or evidence. Its fixed timestamps and values exist only to exercise the Version 0.3.0 record architecture from participants and environment through raw records, coded events, opportunity, trace, measures, uncertainty, and explicit empty advanced layers. `invalid-missing-environment.json` is a negative structural fixture. It omits the required `environments` collection and intentionally leaves other nested objects incomplete. The dependency-free validator must accept its JSON syntax but reject it as a required-field-complete study. These checks are deliberately rudimentary. They do not implement all JSON Schema 2020-12 keywords, resolve identifiers, validate date-time semantics, or establish empirical validity. ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/data/invalid-missing-environment.json (18 lines, 0.4 KiB) ======================================================================== { "study_id": "CIS-EX-008-INVALID-MISSING-ENVIRONMENT", "schema_version": "0.3.0", "study_version": "0.1.0", "theory_version": "1.0.0", "protocol_ref": { "id": "CIS-EX-008-PROTOCOL", "version": "0.1.0" }, "contract_refs": {}, "scope": {}, "construct_refs": [], "participants": [], "interaction_episodes": [], "states": [], "records": [], "coded_events": [], "behavioral_traces": [], "measures": [], "uncertainties": [] } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008/data/valid-synthetic-study.json (403 lines, 19.3 KiB) ======================================================================== { "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "schema_version": "0.3.0", "study_version": "0.1.0", "theory_version": "1.0.0", "protocol_ref": { "id": "CIS-EX-008-PROTOCOL", "version": "0.1.0" }, "contract_refs": { "interaction": { "id": "CIS-EX-008-INTERACTION", "version": "0.2.0" }, "projection": { "id": "CIS-EX-008-PROJECTION-SIGNALED", "version": "0.2.0" }, "opportunity": { "id": "CIS-EX-008-OPPORTUNITY", "version": "0.2.0" }, "behavioral_evidence": { "id": "CIS-EX-008-BEHAVIORAL-EVIDENCE", "version": "0.2.0" }, "measurement": { "id": "CIS-EX-008-MEASUREMENT-DISCOVERY", "version": "0.2.0" }, "similarity": null, "transfer": null, "strategy": null, "prediction": null, "comparison": null }, "scope": { "population": "synthetic participant fixture; no human observation", "task": "bounded target-operation discovery task", "projection": "CIS-EX-008 signaled condition fixture", "context": "schema and lineage validation only" }, "construct_refs": [ { "label": "Interaction episode", "identifier_status": "unratified", "canonical_id": null }, { "label": "Opportunity profile", "identifier_status": "unratified", "canonical_id": null } ], "participants": [ { "participant_id": "CIS-EX-008-P-SYNTHETIC", "participant_kind": "person", "roles": ["study participant"], "capabilities": ["invoke target operation"], "authority": ["target operation", "recovery operation"], "pseudonymous": true, "consent_ref": "CIS-EX-008-CONSENT-SYNTHETIC-NOT-A-HUMAN-RECORD", "local_state_schema_ref": null }, { "participant_id": "CIS-EX-008-TARGET-SYSTEM", "participant_kind": "computational_process", "roles": ["target system"], "capabilities": ["apply frozen transition semantics", "emit feedback"], "authority": ["commit valid target transitions"], "pseudonymous": false, "consent_ref": null, "local_state_schema_ref": "CIS-EX-008-STATE-SCHEMA" } ], "environments": [ { "environment_id": "CIS-EX-008-ENV-SYNTHETIC", "version": "0.1.0", "boundary": "synthetic host, target state, projection, event recorder, and monotonic fixture clock", "state_schema_ref": "CIS-EX-008-STATE-SCHEMA", "authority": ["CIS-EX-008 proposed protocol"], "sensitive_context": false, "provenance": { "source_id": "CIS-EX-008-SYNTHETIC-GENERATOR", "method": "hand-authored deterministic validation fixture", "recorded_at": "2000-01-01T00:00:00Z", "software_version": "0.1.0", "instrument_version": null } } ], "interaction_episodes": [ { "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "interaction_contract_ref": { "id": "CIS-EX-008-INTERACTION", "version": "0.2.0" }, "participant_refs": ["CIS-EX-008-P-SYNTHETIC", "CIS-EX-008-TARGET-SYSTEM"], "boundary": "projection ready through explicit completion", "timescale": "synthetic monotonic episode", "start_time": "2000-01-01T00:00:00Z", "end_time": "2000-01-01T00:00:03Z", "initial_state_ref": "CIS-EX-008-STATE-000", "final_state_ref": "CIS-EX-008-STATE-001", "interaction_status": "candidate", "coupling_evidence_refs": ["CIS-EX-008-EVENT-SELECT", "CIS-EX-008-EVENT-FEEDBACK"], "reciprocal_constraint_evidence_refs": ["CIS-EX-008-EVENT-COMPLETE"], "completion_status": "synthetic criterion satisfied" } ], "states": [ { "state_id": "CIS-EX-008-STATE-000", "payload_schema_ref": "CIS-EX-008-STATE-SCHEMA", "payload": { "target_complete": false }, "provenance": { "source_id": "CIS-EX-008-TARGET-SYSTEM", "method": "synthetic initial state", "recorded_at": "2000-01-01T00:00:00Z", "software_version": "0.1.0", "instrument_version": null } }, { "state_id": "CIS-EX-008-STATE-001", "payload_schema_ref": "CIS-EX-008-STATE-SCHEMA", "payload": { "target_complete": true }, "provenance": { "source_id": "CIS-EX-008-TARGET-SYSTEM", "method": "synthetic committed transition", "recorded_at": "2000-01-01T00:00:02Z", "software_version": "0.1.0", "instrument_version": null } } ], "records": [ { "record_id": "CIS-EX-008-REC-READY", "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "participant_ref": null, "timestamp": "2000-01-01T00:00:00Z", "record_type": "projection.ready", "source": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "payload_schema_ref": "CIS-EX-008-EVENT-PAYLOAD-SCHEMA", "payload": { "projection_ref": "CIS-EX-008-PROJECTION-SIGNALED" }, "missingness": "not_missing", "quality_flags": [], "provenance": { "source_id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "method": "synthetic fixture event", "recorded_at": "2000-01-01T00:00:00Z", "software_version": "0.1.0", "instrument_version": "0.1.0" } }, { "record_id": "CIS-EX-008-REC-BELIEF", "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "participant_ref": "CIS-EX-008-P-SYNTHETIC", "timestamp": "2000-01-01T00:00:01Z", "record_type": "belief.report", "source": "CIS-EX-008-BELIEF-INSTRUMENT", "payload_schema_ref": "CIS-EX-008-BELIEF-PAYLOAD-SCHEMA", "payload": { "response": "yes" }, "missingness": "not_missing", "quality_flags": [], "provenance": { "source_id": "CIS-EX-008-BELIEF-INSTRUMENT", "method": "synthetic fixture response", "recorded_at": "2000-01-01T00:00:01Z", "software_version": null, "instrument_version": "0.1.0" } }, { "record_id": "CIS-EX-008-REC-SELECT", "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "participant_ref": "CIS-EX-008-P-SYNTHETIC", "timestamp": "2000-01-01T00:00:02Z", "record_type": "action.select", "source": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "payload_schema_ref": "CIS-EX-008-EVENT-PAYLOAD-SCHEMA", "payload": { "action_ref": "CIS-EX-008-ACTION-TARGET", "prompted": false }, "missingness": "not_missing", "quality_flags": [], "provenance": { "source_id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "method": "synthetic fixture event", "recorded_at": "2000-01-01T00:00:02Z", "software_version": "0.1.0", "instrument_version": "0.1.0" } }, { "record_id": "CIS-EX-008-REC-FEEDBACK", "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "participant_ref": null, "timestamp": "2000-01-01T00:00:02.010Z", "record_type": "feedback.present", "source": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "payload_schema_ref": "CIS-EX-008-EVENT-PAYLOAD-SCHEMA", "payload": { "result": "transition committed", "state_ref": "CIS-EX-008-STATE-001" }, "missingness": "not_missing", "quality_flags": [], "provenance": { "source_id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "method": "synthetic fixture event", "recorded_at": "2000-01-01T00:00:02.010Z", "software_version": "0.1.0", "instrument_version": "0.1.0" } }, { "record_id": "CIS-EX-008-REC-COMPLETE", "study_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "participant_ref": "CIS-EX-008-P-SYNTHETIC", "timestamp": "2000-01-01T00:00:03Z", "record_type": "task.complete", "source": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "payload_schema_ref": "CIS-EX-008-EVENT-PAYLOAD-SCHEMA", "payload": { "criterion": true }, "missingness": "not_missing", "quality_flags": [], "provenance": { "source_id": "CIS-EX-008-INSTRUMENT-EVENT-LOG", "method": "synthetic fixture event", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": "0.1.0" } } ], "coded_events": [ { "event_id": "CIS-EX-008-EVENT-READY", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "record_refs": ["CIS-EX-008-REC-READY"], "event_type": "projection.ready", "participant_refs": ["CIS-EX-008-TARGET-SYSTEM"], "coding_level": "verified_observation", "coding_rules_ref": { "id": "CIS-EX-008-CODING-RULES", "version": "0.1.0" }, "coder_refs": ["CIS-EX-008-DETERMINISTIC-CODER"], "coding_status": "provisional", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "provenance": { "source_id": "CIS-EX-008-REC-READY", "method": "synthetic deterministic coding", "recorded_at": "2000-01-01T00:00:00Z", "software_version": "0.1.0", "instrument_version": null } }, { "event_id": "CIS-EX-008-EVENT-BELIEF", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "record_refs": ["CIS-EX-008-REC-BELIEF"], "event_type": "belief.report", "participant_refs": ["CIS-EX-008-P-SYNTHETIC"], "coding_level": "verified_observation", "coding_rules_ref": { "id": "CIS-EX-008-CODING-RULES", "version": "0.1.0" }, "coder_refs": ["CIS-EX-008-DETERMINISTIC-CODER"], "coding_status": "provisional", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "provenance": { "source_id": "CIS-EX-008-REC-BELIEF", "method": "synthetic deterministic coding", "recorded_at": "2000-01-01T00:00:01Z", "software_version": "0.1.0", "instrument_version": null } }, { "event_id": "CIS-EX-008-EVENT-SELECT", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "record_refs": ["CIS-EX-008-REC-SELECT"], "event_type": "action.select", "participant_refs": ["CIS-EX-008-P-SYNTHETIC"], "coding_level": "attributed_action", "coding_rules_ref": { "id": "CIS-EX-008-CODING-RULES", "version": "0.1.0" }, "coder_refs": ["CIS-EX-008-DETERMINISTIC-CODER"], "coding_status": "provisional", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "provenance": { "source_id": "CIS-EX-008-REC-SELECT", "method": "synthetic deterministic coding", "recorded_at": "2000-01-01T00:00:02Z", "software_version": "0.1.0", "instrument_version": null } }, { "event_id": "CIS-EX-008-EVENT-FEEDBACK", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "record_refs": ["CIS-EX-008-REC-FEEDBACK"], "event_type": "feedback.present", "participant_refs": ["CIS-EX-008-TARGET-SYSTEM", "CIS-EX-008-P-SYNTHETIC"], "coding_level": "coded_observation", "coding_rules_ref": { "id": "CIS-EX-008-CODING-RULES", "version": "0.1.0" }, "coder_refs": ["CIS-EX-008-DETERMINISTIC-CODER"], "coding_status": "provisional", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "provenance": { "source_id": "CIS-EX-008-REC-FEEDBACK", "method": "synthetic deterministic coding", "recorded_at": "2000-01-01T00:00:02.010Z", "software_version": "0.1.0", "instrument_version": null } }, { "event_id": "CIS-EX-008-EVENT-COMPLETE", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "record_refs": ["CIS-EX-008-REC-COMPLETE"], "event_type": "task.complete", "participant_refs": ["CIS-EX-008-P-SYNTHETIC", "CIS-EX-008-TARGET-SYSTEM"], "coding_level": "coded_observation", "coding_rules_ref": { "id": "CIS-EX-008-CODING-RULES", "version": "0.1.0" }, "coder_refs": ["CIS-EX-008-DETERMINISTIC-CODER"], "coding_status": "provisional", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "provenance": { "source_id": "CIS-EX-008-REC-COMPLETE", "method": "synthetic deterministic coding", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } } ], "opportunity_profiles": [ { "profile_id": "CIS-EX-008-OPP-SYNTHETIC-001", "contract_ref": { "id": "CIS-EX-008-OPPORTUNITY", "version": "0.2.0" }, "participant_ref": "CIS-EX-008-P-SYNTHETIC", "action_ref": "CIS-EX-008-ACTION-TARGET", "state_ref": "CIS-EX-008-STATE-000", "projection_ref": "CIS-EX-008-PROJECTION-SIGNALED", "time": "2000-01-01T00:00:01Z", "domain_valid": { "status": "true", "evidence_refs": ["CIS-EX-008-TARGET"], "uncertainty_ref": null }, "capable": { "status": "true", "evidence_refs": ["CIS-EX-008-P-SYNTHETIC"], "uncertainty_ref": null }, "permitted": { "status": "true", "evidence_refs": ["CIS-EX-008-AUTHORITY-MAP"], "uncertainty_ref": null }, "enabled": { "status": "true", "evidence_refs": ["CIS-EX-008-STATE-000"], "uncertainty_ref": null }, "reachable": { "status": "true", "evidence_refs": ["CIS-EX-008-TRANSITION-SEMANTICS"], "uncertainty_ref": null }, "exposed": { "status": "true", "evidence_refs": ["CIS-EX-008-PROJECTION-SIGNALED"], "uncertainty_ref": null }, "signaled": { "status": "true", "evidence_refs": ["CIS-EX-008-PROJECTION-SIGNALED"], "uncertainty_ref": null }, "believed_available": { "status": "true", "evidence_refs": ["CIS-EX-008-REC-BELIEF"], "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC" }, "selected": { "status": "true", "evidence_refs": ["CIS-EX-008-EVENT-SELECT"], "uncertainty_ref": null }, "executed": { "status": "true", "evidence_refs": ["CIS-EX-008-REC-FEEDBACK"], "uncertainty_ref": null }, "successful": { "status": "true", "evidence_refs": ["CIS-EX-008-EVENT-COMPLETE"], "uncertainty_ref": null }, "reversible": { "status": "unknown", "evidence_refs": [], "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "rationale": "recovery operation not exercised in this fixture" }, "expected_consequence": null, "provenance": { "source_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "method": "synthetic profile assembly", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } } ], "behavioral_traces": [ { "trace_id": "CIS-EX-008-TRACE-SYNTHETIC-001", "episode_id": "CIS-EX-008-EP-SYNTHETIC-001", "behavioral_evidence_contract_ref": { "id": "CIS-EX-008-BEHAVIORAL-EVIDENCE", "version": "0.2.0" }, "event_refs": ["CIS-EX-008-EVENT-READY", "CIS-EX-008-EVENT-BELIEF", "CIS-EX-008-EVENT-SELECT", "CIS-EX-008-EVENT-FEEDBACK", "CIS-EX-008-EVENT-COMPLETE"], "ordering": "total", "ordering_relations": [], "segmentation_version": "0.1.0", "attribution_status": "formal_only", "alternative_explanations": ["synthetic fixture has no behavioral evidentiary force"], "uncertainty_refs": ["CIS-EX-008-UNCERTAINTY-SYNTHETIC"], "provenance": { "source_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "method": "synthetic ordered trace", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } } ], "measures": [ { "measure_id": "CIS-EX-008-MEASURE-DISCOVERY-SYNTHETIC", "measurement_contract_ref": { "id": "CIS-EX-008-MEASUREMENT-DISCOVERY", "version": "0.2.0" }, "measurand": "unprompted discovery event", "level_of_analysis": "participant-condition episode", "scale_type": "binary", "value": { "value_type": "boolean", "value": true, "unit": null }, "missingness": "not_missing", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "evidence_refs": ["CIS-EX-008-EVENT-SELECT"], "interpretation_status": "descriptive", "provenance": { "source_id": "CIS-EX-008-EVENT-SELECT", "method": "synthetic deterministic derivation", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } }, { "measure_id": "CIS-EX-008-MEASURE-INVALID-ATTEMPT-SYNTHETIC", "measurement_contract_ref": { "id": "CIS-EX-008-MEASUREMENT-INVALID-ATTEMPT", "version": "0.2.0" }, "measurand": "attempted unavailable action count", "level_of_analysis": "participant-condition episode", "scale_type": "count", "value": { "value_type": "integer", "value": 0, "unit": "attempts" }, "missingness": "not_missing", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "evidence_refs": ["CIS-EX-008-TRACE-SYNTHETIC-001"], "interpretation_status": "descriptive", "provenance": { "source_id": "CIS-EX-008-TRACE-SYNTHETIC-001", "method": "synthetic deterministic count", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } }, { "measure_id": "CIS-EX-008-MEASURE-RECOVERY-SYNTHETIC", "measurement_contract_ref": { "id": "CIS-EX-008-MEASUREMENT-RECOVERY", "version": "0.2.0" }, "measurand": "recovery duration", "level_of_analysis": "recovery interval", "scale_type": "duration", "value": { "value_type": "duration", "value": null, "unit": "milliseconds" }, "missingness": "not_applicable", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "evidence_refs": [], "interpretation_status": "descriptive", "provenance": { "source_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "method": "no qualifying failure in synthetic fixture", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } }, { "measure_id": "CIS-EX-008-MEASURE-COMPLETION-SYNTHETIC", "measurement_contract_ref": { "id": "CIS-EX-008-MEASUREMENT-COMPLETION", "version": "0.2.0" }, "measurand": "task completion", "level_of_analysis": "participant-condition episode", "scale_type": "binary", "value": { "value_type": "boolean", "value": true, "unit": null }, "missingness": "not_missing", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "evidence_refs": ["CIS-EX-008-EVENT-COMPLETE", "CIS-EX-008-STATE-001"], "interpretation_status": "descriptive", "provenance": { "source_id": "CIS-EX-008-EVENT-COMPLETE", "method": "synthetic deterministic criterion", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } }, { "measure_id": "CIS-EX-008-MEASURE-BELIEF-SYNTHETIC", "measurement_contract_ref": { "id": "CIS-EX-008-MEASUREMENT-BELIEF", "version": "0.2.0" }, "measurand": "reported believed availability", "level_of_analysis": "participant-condition report", "scale_type": "nominal", "value": { "value_type": "category", "value": "yes", "unit": null }, "missingness": "not_missing", "uncertainty_ref": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "evidence_refs": ["CIS-EX-008-EVENT-BELIEF"], "interpretation_status": "descriptive", "provenance": { "source_id": "CIS-EX-008-EVENT-BELIEF", "method": "synthetic categorical mapping", "recorded_at": "2000-01-01T00:00:03Z", "software_version": "0.1.0", "instrument_version": null } } ], "uncertainties": [ { "uncertainty_id": "CIS-EX-008-UNCERTAINTY-SYNTHETIC", "kind": "qualitative", "representation": { "status": "synthetic fixture only", "empirical_force": "none" }, "coverage": null, "assumptions": ["All timestamps and records are deterministic invented fixture values.", "No participant or empirical observation exists."], "provenance": { "source_id": "CIS-EX-008-SYNTHETIC-FIXTURE", "method": "fixture limitation declaration", "recorded_at": "2000-01-01T00:00:00Z", "software_version": "0.1.0", "instrument_version": null } } ], "similarity_profiles": [], "transfer_records": [], "strategy_hypotheses": [], "prediction_records": [], "comparison_profiles": [], "deviations": [] } ======================================================================== ## FILE: app/examples/studies/CIS-EX-008_projection-signaling-study.md (82 lines, 3.9 KiB) ======================================================================== # CIS-EX-008 — Projection Signaling Study Protocol **Theory version:** 1.0.0 **Protocol version:** 0.1.0 **Status:** proposed, not preregistered or frozen ## Research question Holding target semantics and feasible operations constant, how do changes in projection exposure and signaling affect discovery, believed availability, action selection, invalid attempts, completion, and recovery? ## Design Use a within-participant, counterbalanced comparison of two projections over the same deterministic target and operation set. One projection exposes and signals the target operation; the other exposes it without the target signifier. Match latency, instructions, available operations, state transitions, success criteria, and feedback after execution. Randomize condition order using a seed recorded in the frozen preregistration. Separate training tasks from measured tasks and insert a transfer task to detect carryover. Population, accessibility accommodations, sample size, recruitment, device constraints, task content, and stopping thresholds remain unset until methods, accessibility, and ethics review. Sample size must follow a preregistered precision or power analysis; this protocol does not invent a count. ## Required contract instances - Projection Contract for each condition; - Opportunity Contract defining actual and believed availability separately; - Interaction Contract defining episode boundary, failure, completion, and recovery; - Behavioral Evidence Contract defining records, detection, coding, attribution, alternatives, missingness, and adjudication; - Measurement Contract for each outcome; - optional Prediction Contract only if an out-of-sample forecast is registered. All instances must validate, use immutable versions, and retain unratified concept identifiers as null until ratification. Draft contract labels do not license collection. Draft 0.2.0 instances are maintained under `CIS-EX-008/contracts/`: two Projection Contracts, one Opportunity Contract, one Interaction Contract, one Behavioral Evidence Contract, and separate Measurement Contracts for discovery, invalid attempts, recovery, completion, and believed availability. Their README records the exact mapping and structural validation boundary. `CIS-EX-008/data/` contains one explicitly synthetic Version 0.3.0 lineage fixture and one intentionally invalid missing-environment fixture. Neither is an observation or a substitute for an instrument pilot. ## Direct records and derived variables Instrument records: projection shown, operation exposure, signifier state, timestamp, selected operation, execution result, feedback, state transition, task completion, abandonment, and recovery transition. Derived only under frozen rules: unprompted discovery event, prompted discovery, invalid attempt, path length, recovery duration, and completion. Believed availability, expected consequence, perceived reversibility, and confidence are participant reports or latent measures, never inferred from non-selection. ## Analysis boundary Estimate condition effects with participant-level repeated structure, order and carryover terms, effect sizes, uncertainty, missingness sensitivity, and the preregistered equivalence bounds. Compare a baseline state-and-trace model with typed opportunity variables only out of sample. Preserve confirmatory and exploratory analyses separately and append deviations. Equal completion does not establish equal discovery, understanding, accessibility, trust, or interaction equivalence. A signaling effect does not establish a universal perceptual mechanism or transport beyond the declared population, task, projection, device, and context. ## Freeze gate Preregistration is blocked until canonical concept identifiers, study-specific governance, consent, instruments, coding rules, manipulation checks, sample-size rationale, accessibility review, analysis code, and independent methods review are complete. No participant collection is authorized by this example. ======================================================================== ## FILE: app/examples/visualizations/evidence-inference-ladder.html (1089 lines, 37.5 KiB) ======================================================================== Evidence Inference Ladder ======================================================================== ## FILE: app/examples/visualizations/interaction-substrate-lab.html (1372 lines, 56.2 KiB) ======================================================================== Interaction Substrate Lab ======================================================================== ## FILE: app/examples/visualizations/projection-invariance-workbench.html (1122 lines, 39.3 KiB) ======================================================================== Projection Invariance Workbench ======================================================================== ## FILE: app/examples/visualizations/src/evidence-inference-ladder.html (94 lines, 7.3 KiB) ========================================================================
CIS-EX-005Evidence and inference ladder·Measurement Handbook
What was recorded?→What was established?→How far may the claim go?
Recorded event · fixed input
record_typecontrol.activate
participantP-017
latency240 ms
resultcompleted
Evidence gates · each licenses only the next level
Highest defensible statement
======================================================================== ## FILE: app/examples/visualizations/src/interaction-substrate-lab.html (377 lines, 22.8 KiB) ========================================================================
CIS-EX-003Executable concept model·Theory Version 1.0.0
Can it happen?→Can this participant find it?→What actually occurred?
System now
A door shows the current open and locked state. closed · unlocked
Positionclosed
Lockreleased
Projectionopen signaled
Checking C reference vector
System can execute this action now
Action is available through this projection
Participant belief matches projected availability
Why · each dimension answers a different question
What happened · selection is not execution; execution is not success
Events appear in participant lanes as actions are attempted.
No action selected in this episode.
======================================================================== ## FILE: app/examples/visualizations/src/projection-invariance-workbench.html (127 lines, 8.7 KiB) ========================================================================
CIS-EX-004Projection and invariance workbench·Theory Version 1.0.0
What stayed the same?→What changed?→Which comparison is licensed?
Target state · authority
temperature_c20
alarmactive
modeautomatic
All comparison claims are relative to these declared fields.
Projection A · operations
temperature_c20 · preserved
alarmactive · preserved
modeomitted
Observer: trained operator · task: alarm response
Projection B · adjustable
Every transform, omission, and introduction remains visible.
======================================================================== ## FILE: app/include/cis.h (260 lines, 8.0 KiB) ======================================================================== #ifndef CIS_H #define CIS_H #include #include #define CIS_API_VERSION_MAJOR 0u #define CIS_API_VERSION_MINOR 1u #define CIS_API_VERSION_PATCH 0u #define CIS_TRACE_SCHEMA_VERSION 1u #define CIS_NAME_CAP 32u #define CIS_MAX_STATE 16u #define CIS_MAX_ACTIONS 16u #define CIS_MAX_PARTICIPANTS 16u #define CIS_MAX_PRECONDITIONS 8u #define CIS_MAX_EFFECTS 8u #define CIS_MAX_INVARIANTS 8u #define CIS_MAX_PROJECTION_FIELDS 16u #define CIS_MAX_TRACE 128u #define CIS_MAX_SEARCH_STATES 128u #define CIS_MAX_HORIZON 16u typedef enum { CIS_OK = 0, CIS_ERR_ARGUMENT, CIS_ERR_CAPACITY, CIS_ERR_DUPLICATE, CIS_ERR_NOT_FOUND, CIS_ERR_BOUNDS, CIS_ERR_CAPABILITY, CIS_ERR_PERMISSION, CIS_ERR_DISABLED, CIS_ERR_INVARIANT, CIS_ERR_OVERFLOW, CIS_ERR_REPLAY_DIVERGED } CisResult; typedef enum { CIS_PRED_EQ = 0, CIS_PRED_NE, CIS_PRED_LT, CIS_PRED_LE, CIS_PRED_GT, CIS_PRED_GE } CisPredicateOp; typedef enum { CIS_EFFECT_SET = 0, CIS_EFFECT_ADD } CisEffectOp; typedef enum { CIS_EVENT_REJECTED = 0, CIS_EVENT_EXECUTED = 1 } CisEventStatus; typedef enum { CIS_OUTCOME_UNKNOWN = 0, CIS_OUTCOME_FAILURE, CIS_OUTCOME_SUCCESS } CisOutcome; typedef enum { CIS_FIELD_PRESERVED = 0, CIS_FIELD_TRANSFORMED, CIS_FIELD_INTRODUCED } CisProjectionKind; typedef struct { char name[CIS_NAME_CAP]; int64_t minimum; int64_t maximum; } CisStateVariable; typedef struct { int64_t values[CIS_MAX_STATE]; uint8_t count; } CisState; typedef struct { uint8_t state_index; CisPredicateOp operation; int64_t value; } CisPredicate; typedef struct { uint8_t state_index; CisEffectOp operation; int64_t value; } CisEffect; typedef struct { char name[CIS_NAME_CAP]; uint32_t required_capabilities; uint32_t permitted_roles; CisPredicate preconditions[CIS_MAX_PRECONDITIONS]; uint8_t precondition_count; CisEffect effects[CIS_MAX_EFFECTS]; uint8_t effect_count; int8_t reverse_action; } CisAction; typedef struct { char name[CIS_NAME_CAP]; uint8_t role; uint32_t capabilities; } CisParticipant; typedef struct { CisStateVariable variables[CIS_MAX_STATE]; uint8_t variable_count; CisAction actions[CIS_MAX_ACTIONS]; uint8_t action_count; CisPredicate invariants[CIS_MAX_INVARIANTS]; uint8_t invariant_count; } CisDomain; typedef struct { char name[CIS_NAME_CAP]; int8_t source_state_index; int64_t multiplier; int64_t offset; CisProjectionKind kind; } CisProjectionField; typedef struct { CisProjectionField fields[CIS_MAX_PROJECTION_FIELDS]; uint8_t field_count; uint32_t exposed_actions; uint32_t signaled_actions; } CisProjection; typedef struct { int64_t values[CIS_MAX_PROJECTION_FIELDS]; CisProjectionField fields[CIS_MAX_PROJECTION_FIELDS]; uint8_t count; uint32_t omitted_state; } CisProjectedState; typedef struct { uint16_t schema_version; uint32_t sequence; uint64_t tick; uint8_t participant_index; uint8_t action_index; CisEventStatus status; CisOutcome outcome; CisResult result; uint64_t before_hash; uint64_t after_hash; } CisEvent; typedef struct { CisDomain domain; CisParticipant participants[CIS_MAX_PARTICIPANTS]; uint8_t participant_count; CisState initial_state; CisState state; CisEvent trace[CIS_MAX_TRACE]; uint16_t trace_count; } CisSystem; typedef struct { uint8_t domain_valid; uint8_t capable; uint8_t permitted; uint8_t enabled; uint8_t reachable; uint8_t exposed; uint8_t signaled; uint8_t believed_available; uint8_t selected; uint8_t executed; uint8_t successful; uint8_t reversible; uint16_t belief_confidence_permyriad; int64_t expected_consequence; uint16_t uncertainty_permyriad; } CisOpportunity; typedef struct { uint8_t comparable; uint8_t equivalent; uint16_t similarity_permyriad; } CisComparison; void cis_domain_init(CisDomain *domain); CisResult cis_domain_add_variable(CisDomain *domain, const char *name, int64_t minimum, int64_t maximum, uint8_t *index_out); CisResult cis_domain_add_action(CisDomain *domain, const CisAction *action, uint8_t *index_out); CisResult cis_domain_add_invariant(CisDomain *domain, CisPredicate invariant); void cis_action_init(CisAction *action, const char *name); CisResult cis_action_add_precondition(CisAction *action, CisPredicate predicate); CisResult cis_action_add_effect(CisAction *action, CisEffect effect); CisResult cis_system_init(CisSystem *system, const CisDomain *domain, const CisState *initial_state); CisResult cis_system_add_participant(CisSystem *system, const char *name, uint8_t role, uint32_t capabilities, uint8_t *index_out); CisResult cis_execute(CisSystem *system, uint8_t participant_index, uint8_t action_index, uint64_t tick); CisResult cis_record_outcome(CisSystem *system, uint32_t sequence, CisOutcome outcome); CisResult cis_replay(const CisSystem *system, CisState *state_out); uint64_t cis_state_hash(const CisState *state); void cis_projection_init(CisProjection *projection); CisResult cis_projection_add_field(CisProjection *projection, const char *name, int8_t source_state_index, int64_t multiplier, int64_t offset, CisProjectionKind kind); CisResult cis_project(const CisProjection *projection, const CisState *state, CisProjectedState *projected_out); CisResult cis_reachable(const CisDomain *domain, const CisState *initial, const CisPredicate *target, uint8_t role, uint32_t capabilities, uint8_t horizon, uint8_t *reachable_out); CisResult cis_opportunity(const CisSystem *system, const CisProjection *projection, uint8_t participant_index, uint8_t action_index, uint8_t believed_available, uint16_t belief_confidence_permyriad, int64_t expected_consequence, uint16_t uncertainty_permyriad, const CisPredicate *reachable_target, uint8_t horizon, CisOpportunity *out); CisComparison cis_compare_states(const CisDomain *domain, const CisState *left, const CisState *right); CisComparison cis_compare_projections(const CisProjectedState *left, const CisProjectedState *right); CisComparison cis_compare_traces(const CisEvent *left, uint16_t left_count, const CisEvent *right, uint16_t right_count, const uint8_t *participant_map, uint8_t participant_map_count, const uint8_t *action_map, uint8_t action_map_count); uint16_t cis_measure_action_frequency(const CisSystem *system, uint8_t action_index); uint64_t cis_measure_elapsed(const CisSystem *system); uint8_t cis_measure_completion(const CisState *state, const CisPredicate *completion); CisResult cis_measure_recovery(const CisSystem *system, uint32_t after_sequence, const CisPredicate *recovered, uint64_t *ticks_out); uint16_t cis_measure_opportunity_mismatch(const CisOpportunity *opportunity); uint8_t cis_trace_has_aba_recurrence_pattern(const CisSystem *system); const char *cis_result_name(CisResult result); #endif ======================================================================== ## FILE: app/release-manifest.json (265 lines, 8.3 KiB) 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unratified", "bibliography and evidence mappings are not authority-verified", "schemas are unpiloted draft 0.x candidates", "legacy Markdown derivatives are not regenerated", "no empirical or independent review is recorded" ] } ======================================================================== ## FILE: app/src/cis.c (1005 lines, 34.4 KiB) ======================================================================== #include "cis.h" #include static void zero_bytes(void *target, size_t count) { volatile uint8_t *bytes = (volatile uint8_t *)target; size_t index; for (index = 0u; index < count; ++index) { bytes[index] = 0u; } } static void copy_bytes(void *target, const void *source, size_t count) { volatile uint8_t *destination = (volatile uint8_t *)target; const volatile uint8_t *origin = (const volatile uint8_t *)source; size_t index; for (index = 0u; index < count; ++index) { destination[index] = origin[index]; } } static int name_copy(char target[CIS_NAME_CAP], const char *source) { size_t index = 0u; if (source == NULL || source[0] == '\0') { return 0; } while (source[index] != '\0' && index + 1u < CIS_NAME_CAP) { target[index] = source[index]; ++index; } if (source[index] != '\0') { target[0] = '\0'; return 0; } target[index] = '\0'; return 1; } static int name_equal(const char *left, const char *right) { size_t index = 0u; while (left[index] != '\0' && right[index] != '\0') { if (left[index] != right[index]) { return 0; } ++index; } return left[index] == right[index]; } static int predicate_holds(const CisState *state, const CisPredicate *predicate) { int64_t actual; if (state == NULL || predicate == NULL || predicate->state_index >= state->count) { return 0; } actual = state->values[predicate->state_index]; switch (predicate->operation) { case CIS_PRED_EQ: return actual == predicate->value; case CIS_PRED_NE: return actual != predicate->value; case CIS_PRED_LT: return actual < predicate->value; case CIS_PRED_LE: return actual <= predicate->value; case CIS_PRED_GT: return actual > predicate->value; case CIS_PRED_GE: return actual >= predicate->value; default: return 0; } } static CisResult state_valid(const CisDomain *domain, const CisState *state) { uint8_t index; if (domain == NULL || state == NULL || state->count != domain->variable_count) { return CIS_ERR_ARGUMENT; } for (index = 0u; index < state->count; ++index) { if (state->values[index] < domain->variables[index].minimum || state->values[index] > domain->variables[index].maximum) { return CIS_ERR_BOUNDS; } } for (index = 0u; index < domain->invariant_count; ++index) { if (!predicate_holds(state, &domain->invariants[index])) { return CIS_ERR_INVARIANT; } } return CIS_OK; } static int add_i64(int64_t left, int64_t right, int64_t *out) { if ((right > 0 && left > INT64_MAX - right) || (right < 0 && left < INT64_MIN - right)) { return 0; } *out = left + right; return 1; } static int multiply_i64(int64_t left, int64_t right, int64_t *out) { if (left == 0 || right == 0) { *out = 0; return 1; } if ((left == INT64_MIN && right == -1) || (right == INT64_MIN && left == -1)) { return 0; } if (left > 0) { if ((right > 0 && left > INT64_MAX / right) || (right < 0 && right < INT64_MIN / left)) { return 0; } } else if ((right > 0 && left < INT64_MIN / right) || (right < 0 && left < INT64_MAX / right)) { return 0; } *out = left * right; return 1; } static CisResult apply_action(const CisDomain *domain, const CisAction *action, const CisState *before, CisState *after) { uint8_t index; CisResult valid; for (index = 0u; index < action->precondition_count; ++index) { if (!predicate_holds(before, &action->preconditions[index])) { return CIS_ERR_DISABLED; } } *after = *before; for (index = 0u; index < action->effect_count; ++index) { const CisEffect *effect = &action->effects[index]; int64_t value; if (effect->state_index >= after->count) { return CIS_ERR_ARGUMENT; } if (effect->operation == CIS_EFFECT_SET) { value = effect->value; } else if (effect->operation == CIS_EFFECT_ADD) { if (!add_i64(after->values[effect->state_index], effect->value, &value)) { return CIS_ERR_OVERFLOW; } } else { return CIS_ERR_ARGUMENT; } after->values[effect->state_index] = value; } valid = state_valid(domain, after); return valid; } void cis_domain_init(CisDomain *domain) { if (domain != NULL) { zero_bytes(domain, sizeof(*domain)); } } CisResult cis_domain_add_variable(CisDomain *domain, const char *name, int64_t minimum, int64_t maximum, uint8_t *index_out) { uint8_t index; CisStateVariable *variable; if (domain == NULL || name == NULL || minimum > maximum) { return CIS_ERR_ARGUMENT; } if (domain->variable_count >= CIS_MAX_STATE) { return CIS_ERR_CAPACITY; } for (index = 0u; index < domain->variable_count; ++index) { if (name_equal(domain->variables[index].name, name)) { return CIS_ERR_DUPLICATE; } } variable = &domain->variables[domain->variable_count]; if (!name_copy(variable->name, name)) { return CIS_ERR_ARGUMENT; } variable->minimum = minimum; variable->maximum = maximum; if (index_out != NULL) { *index_out = domain->variable_count; } ++domain->variable_count; return CIS_OK; } void cis_action_init(CisAction *action, const char *name) { if (action != NULL) { zero_bytes(action, sizeof(*action)); action->reverse_action = -1; if (name != NULL) { (void)name_copy(action->name, name); } } } CisResult cis_action_add_precondition(CisAction *action, CisPredicate predicate) { if (action == NULL || predicate.operation > CIS_PRED_GE) { return CIS_ERR_ARGUMENT; } if (action->precondition_count >= CIS_MAX_PRECONDITIONS) { return CIS_ERR_CAPACITY; } action->preconditions[action->precondition_count++] = predicate; return CIS_OK; } CisResult cis_action_add_effect(CisAction *action, CisEffect effect) { if (action == NULL || effect.operation > CIS_EFFECT_ADD) { return CIS_ERR_ARGUMENT; } if (action->effect_count >= CIS_MAX_EFFECTS) { return CIS_ERR_CAPACITY; } action->effects[action->effect_count++] = effect; return CIS_OK; } CisResult cis_domain_add_action(CisDomain *domain, const CisAction *action, uint8_t *index_out) { uint8_t index; if (domain == NULL || action == NULL || action->name[0] == '\0' || action->precondition_count > CIS_MAX_PRECONDITIONS || action->effect_count > CIS_MAX_EFFECTS || action->reverse_action < -1) { return CIS_ERR_ARGUMENT; } if (domain->action_count >= CIS_MAX_ACTIONS) { return CIS_ERR_CAPACITY; } for (index = 0u; index < domain->action_count; ++index) { if (name_equal(domain->actions[index].name, action->name)) { return CIS_ERR_DUPLICATE; } } for (index = 0u; index < action->precondition_count; ++index) { if (action->preconditions[index].state_index >= domain->variable_count) { return CIS_ERR_ARGUMENT; } } for (index = 0u; index < action->effect_count; ++index) { if (action->effects[index].state_index >= domain->variable_count) { return CIS_ERR_ARGUMENT; } } copy_bytes(&domain->actions[domain->action_count], action, sizeof(*action)); if (index_out != NULL) { *index_out = domain->action_count; } ++domain->action_count; return CIS_OK; } CisResult cis_domain_add_invariant(CisDomain *domain, CisPredicate invariant) { if (domain == NULL || invariant.state_index >= domain->variable_count || invariant.operation > CIS_PRED_GE) { return CIS_ERR_ARGUMENT; } if (domain->invariant_count >= CIS_MAX_INVARIANTS) { return CIS_ERR_CAPACITY; } domain->invariants[domain->invariant_count++] = invariant; return CIS_OK; } CisResult cis_system_init(CisSystem *system, const CisDomain *domain, const CisState *initial_state) { CisResult valid; uint8_t index; if (system == NULL || domain == NULL || initial_state == NULL || domain->variable_count > CIS_MAX_STATE || domain->action_count > CIS_MAX_ACTIONS) { return CIS_ERR_ARGUMENT; } for (index = 0u; index < domain->action_count; ++index) { int8_t reverse = domain->actions[index].reverse_action; if (reverse >= (int8_t)domain->action_count) { return CIS_ERR_ARGUMENT; } } valid = state_valid(domain, initial_state); if (valid != CIS_OK) { return valid; } zero_bytes(system, sizeof(*system)); copy_bytes(&system->domain, domain, sizeof(*domain)); system->initial_state = *initial_state; system->state = *initial_state; return CIS_OK; } CisResult cis_system_add_participant(CisSystem *system, const char *name, uint8_t role, uint32_t capabilities, uint8_t *index_out) { uint8_t index; CisParticipant *participant; if (system == NULL || name == NULL || role >= 32u) { return CIS_ERR_ARGUMENT; } if (system->participant_count >= CIS_MAX_PARTICIPANTS) { return CIS_ERR_CAPACITY; } for (index = 0u; index < system->participant_count; ++index) { if (name_equal(system->participants[index].name, name)) { return CIS_ERR_DUPLICATE; } } participant = &system->participants[system->participant_count]; if (!name_copy(participant->name, name)) { return CIS_ERR_ARGUMENT; } participant->role = role; participant->capabilities = capabilities; if (index_out != NULL) { *index_out = system->participant_count; } ++system->participant_count; return CIS_OK; } uint64_t cis_state_hash(const CisState *state) { uint64_t hash = UINT64_C(14695981039346656037); uint8_t index; uint8_t byte; if (state == NULL) { return 0u; } hash ^= state->count; hash *= UINT64_C(1099511628211); for (index = 0u; index < state->count; ++index) { uint64_t value = (uint64_t)state->values[index]; for (byte = 0u; byte < 8u; ++byte) { hash ^= (value >> (byte * 8u)) & UINT64_C(255); hash *= UINT64_C(1099511628211); } } return hash; } CisResult cis_execute(CisSystem *system, uint8_t participant_index, uint8_t action_index, uint64_t tick) { CisEvent *event; const CisParticipant *participant; const CisAction *action; CisState candidate; CisResult result; if (system == NULL || participant_index >= system->participant_count || action_index >= system->domain.action_count) { return CIS_ERR_ARGUMENT; } if (system->trace_count > 0u && tick < system->trace[system->trace_count - 1u].tick) { return CIS_ERR_ARGUMENT; } if (system->trace_count >= CIS_MAX_TRACE) { return CIS_ERR_CAPACITY; } participant = &system->participants[participant_index]; action = &system->domain.actions[action_index]; event = &system->trace[system->trace_count]; zero_bytes(event, sizeof(*event)); event->schema_version = CIS_TRACE_SCHEMA_VERSION; event->sequence = system->trace_count; event->tick = tick; event->participant_index = participant_index; event->action_index = action_index; event->before_hash = cis_state_hash(&system->state); if ((participant->capabilities & action->required_capabilities) != action->required_capabilities) { result = CIS_ERR_CAPABILITY; } else if ((action->permitted_roles & (UINT32_C(1) << participant->role)) == 0u) { result = CIS_ERR_PERMISSION; } else { result = apply_action(&system->domain, action, &system->state, &candidate); if (result == CIS_OK) { system->state = candidate; event->status = CIS_EVENT_EXECUTED; } } event->result = result; event->after_hash = cis_state_hash(&system->state); ++system->trace_count; return result; } CisResult cis_record_outcome(CisSystem *system, uint32_t sequence, CisOutcome outcome) { CisEvent *event; if (system == NULL || sequence >= system->trace_count || outcome == CIS_OUTCOME_UNKNOWN || outcome > CIS_OUTCOME_SUCCESS) { return CIS_ERR_ARGUMENT; } event = &system->trace[sequence]; if (event->status != CIS_EVENT_EXECUTED) { return CIS_ERR_ARGUMENT; } if (event->outcome != CIS_OUTCOME_UNKNOWN) { return CIS_ERR_DUPLICATE; } event->outcome = outcome; return CIS_OK; } CisResult cis_replay(const CisSystem *system, CisState *state_out) { CisState current; uint16_t index; if (system == NULL || state_out == NULL) { return CIS_ERR_ARGUMENT; } current = system->initial_state; for (index = 0u; index < system->trace_count; ++index) { const CisEvent *event = &system->trace[index]; CisState candidate; CisResult result; if (event->schema_version != CIS_TRACE_SCHEMA_VERSION) { return CIS_ERR_REPLAY_DIVERGED; } if (cis_state_hash(¤t) != event->before_hash) { return CIS_ERR_REPLAY_DIVERGED; } if (event->status == CIS_EVENT_EXECUTED) { if (event->action_index >= system->domain.action_count) { return CIS_ERR_REPLAY_DIVERGED; } result = apply_action(&system->domain, &system->domain.actions[event->action_index], ¤t, &candidate); if (result != CIS_OK) { return CIS_ERR_REPLAY_DIVERGED; } current = candidate; } if (cis_state_hash(¤t) != event->after_hash) { return CIS_ERR_REPLAY_DIVERGED; } } *state_out = current; return CIS_OK; } void cis_projection_init(CisProjection *projection) { if (projection != NULL) { zero_bytes(projection, sizeof(*projection)); } } CisResult cis_projection_add_field(CisProjection *projection, const char *name, int8_t source_state_index, int64_t multiplier, int64_t offset, CisProjectionKind kind) { CisProjectionField *field; uint8_t index; if (projection == NULL || name == NULL || kind > CIS_FIELD_INTRODUCED || (kind == CIS_FIELD_INTRODUCED && source_state_index != -1) || (kind != CIS_FIELD_INTRODUCED && source_state_index < 0) || (kind == CIS_FIELD_PRESERVED && (multiplier != 1 || offset != 0))) { return CIS_ERR_ARGUMENT; } if (projection->field_count >= CIS_MAX_PROJECTION_FIELDS) { return CIS_ERR_CAPACITY; } for (index = 0u; index < projection->field_count; ++index) { if (name_equal(projection->fields[index].name, name)) { return CIS_ERR_DUPLICATE; } } field = &projection->fields[projection->field_count]; if (!name_copy(field->name, name)) { return CIS_ERR_ARGUMENT; } field->source_state_index = source_state_index; field->multiplier = multiplier; field->offset = offset; field->kind = kind; ++projection->field_count; return CIS_OK; } CisResult cis_project(const CisProjection *projection, const CisState *state, CisProjectedState *projected_out) { uint8_t index; uint32_t observed = 0u; if (projection == NULL || state == NULL || projected_out == NULL) { return CIS_ERR_ARGUMENT; } zero_bytes(projected_out, sizeof(*projected_out)); for (index = 0u; index < projection->field_count; ++index) { const CisProjectionField *field = &projection->fields[index]; int64_t multiplied; int64_t value; if (field->kind == CIS_FIELD_INTRODUCED) { value = field->offset; } else { if (field->source_state_index < 0 || (uint8_t)field->source_state_index >= state->count) { return CIS_ERR_ARGUMENT; } observed |= UINT32_C(1) << (uint8_t)field->source_state_index; if (!multiply_i64(state->values[(uint8_t)field->source_state_index], field->multiplier, &multiplied) || !add_i64(multiplied, field->offset, &value)) { return CIS_ERR_OVERFLOW; } } projected_out->values[index] = value; copy_bytes(&projected_out->fields[index], field, sizeof(*field)); } projected_out->count = projection->field_count; if (state->count == 32u) { projected_out->omitted_state = ~observed; } else { projected_out->omitted_state = ((UINT32_C(1) << state->count) - UINT32_C(1)) & ~observed; } return CIS_OK; } static int state_equal(const CisState *left, const CisState *right) { uint8_t index; if (left->count != right->count) { return 0; } for (index = 0u; index < left->count; ++index) { if (left->values[index] != right->values[index]) { return 0; } } return 1; } CisResult cis_reachable(const CisDomain *domain, const CisState *initial, const CisPredicate *target, uint8_t role, uint32_t capabilities, uint8_t horizon, uint8_t *reachable_out) { CisState states[CIS_MAX_SEARCH_STATES]; uint8_t depths[CIS_MAX_SEARCH_STATES]; uint16_t head = 0u; uint16_t tail = 1u; CisResult valid; if (domain == NULL || initial == NULL || target == NULL || reachable_out == NULL || role >= 32u || horizon > CIS_MAX_HORIZON || target->state_index >= initial->count) { return CIS_ERR_ARGUMENT; } valid = state_valid(domain, initial); if (valid != CIS_OK) { return valid; } *reachable_out = 0u; states[0] = *initial; depths[0] = 0u; while (head < tail) { uint8_t action_index; CisState current = states[head]; uint8_t depth = depths[head]; ++head; if (predicate_holds(¤t, target)) { *reachable_out = 1u; return CIS_OK; } if (depth >= horizon) { continue; } for (action_index = 0u; action_index < domain->action_count; ++action_index) { const CisAction *action = &domain->actions[action_index]; CisState candidate; uint16_t seen; int duplicate = 0; if ((action->permitted_roles & (UINT32_C(1) << role)) == 0u || (capabilities & action->required_capabilities) != action->required_capabilities || apply_action(domain, action, ¤t, &candidate) != CIS_OK) { continue; } for (seen = 0u; seen < tail; ++seen) { if (state_equal(&states[seen], &candidate)) { duplicate = 1; break; } } if (duplicate) { continue; } if (tail >= CIS_MAX_SEARCH_STATES) { return CIS_ERR_CAPACITY; } states[tail] = candidate; depths[tail] = (uint8_t)(depth + 1u); ++tail; } } return CIS_OK; } CisResult cis_opportunity(const CisSystem *system, const CisProjection *projection, uint8_t participant_index, uint8_t action_index, uint8_t believed_available, uint16_t belief_confidence_permyriad, int64_t expected_consequence, uint16_t uncertainty_permyriad, const CisPredicate *reachable_target, uint8_t horizon, CisOpportunity *out) { const CisParticipant *participant; const CisAction *action; uint8_t index; if (system == NULL || projection == NULL || out == NULL || reachable_target == NULL || participant_index >= system->participant_count || action_index >= system->domain.action_count || belief_confidence_permyriad > 10000u || uncertainty_permyriad > 10000u) { return CIS_ERR_ARGUMENT; } zero_bytes(out, sizeof(*out)); participant = &system->participants[participant_index]; action = &system->domain.actions[action_index]; out->domain_valid = 1u; out->capable = (participant->capabilities & action->required_capabilities) == action->required_capabilities; out->permitted = (action->permitted_roles & (UINT32_C(1) << participant->role)) != 0u; out->enabled = 1u; for (index = 0u; index < action->precondition_count; ++index) { if (!predicate_holds(&system->state, &action->preconditions[index])) { out->enabled = 0u; break; } } out->exposed = (projection->exposed_actions & (UINT32_C(1) << action_index)) != 0u; out->signaled = (projection->signaled_actions & (UINT32_C(1) << action_index)) != 0u; out->believed_available = believed_available != 0u; out->belief_confidence_permyriad = belief_confidence_permyriad; out->expected_consequence = expected_consequence; out->uncertainty_permyriad = uncertainty_permyriad; { CisResult result = cis_reachable(&system->domain, &system->state, reachable_target, participant->role, participant->capabilities, horizon, &out->reachable); if (result != CIS_OK) { return result; } } if (action->reverse_action >= 0 && action->reverse_action < (int8_t)system->domain.action_count && out->capable && out->permitted && out->enabled) { const CisAction *reverse = &system->domain.actions[(uint8_t)action->reverse_action]; CisState changed; CisState restored; uint8_t reverse_capable = (participant->capabilities & reverse->required_capabilities) == reverse->required_capabilities; uint8_t reverse_permitted = (reverse->permitted_roles & (UINT32_C(1) << participant->role)) != 0u; out->reversible = reverse_capable && reverse_permitted && apply_action(&system->domain, action, &system->state, &changed) == CIS_OK && apply_action(&system->domain, reverse, &changed, &restored) == CIS_OK && state_equal(&system->state, &restored); } for (index = 0u; index < system->trace_count; ++index) { const CisEvent *event = &system->trace[index]; if (event->participant_index == participant_index && event->action_index == action_index) { out->selected = 1u; if (event->status == CIS_EVENT_EXECUTED) { out->executed = 1u; if (event->outcome == CIS_OUTCOME_SUCCESS) { out->successful = 1u; } } } } return CIS_OK; } static uint64_t unsigned_distance(int64_t left, int64_t right) { if (left >= right) { return (uint64_t)left - (uint64_t)right; } return (uint64_t)right - (uint64_t)left; } static uint16_t ratio_permyriad(uint64_t numerator, uint64_t denominator) { uint64_t quotient = 0u; uint64_t remainder; uint16_t index; if (denominator == 0u || numerator == 0u) { return 0u; } if (numerator >= denominator) { return 10000u; } remainder = numerator; for (index = 0u; index < 10000u; ++index) { if (remainder >= denominator - numerator) { remainder -= denominator - numerator; ++quotient; } else { remainder += numerator; } } return (uint16_t)quotient; } CisComparison cis_compare_states(const CisDomain *domain, const CisState *left, const CisState *right) { CisComparison comparison = {0u, 0u, 0u}; uint32_t loss = 0u; uint8_t index; if (domain == NULL || left == NULL || right == NULL || left->count != domain->variable_count || right->count != domain->variable_count || state_valid(domain, left) != CIS_OK || state_valid(domain, right) != CIS_OK) { return comparison; } comparison.comparable = 1u; comparison.equivalent = (uint8_t)state_equal(left, right); if (domain->variable_count == 0u) { comparison.similarity_permyriad = 10000u; return comparison; } for (index = 0u; index < domain->variable_count; ++index) { uint64_t distance = unsigned_distance(left->values[index], right->values[index]); uint64_t range = unsigned_distance(domain->variables[index].minimum, domain->variables[index].maximum); loss += range == 0u ? (distance == 0u ? 0u : 10000u) : ratio_permyriad(distance, range); } comparison.similarity_permyriad = (uint16_t)(10000u - loss / domain->variable_count); return comparison; } CisComparison cis_compare_projections(const CisProjectedState *left, const CisProjectedState *right) { CisComparison comparison = {0u, 0u, 0u}; uint8_t equal = 0u; uint8_t index; if (left == NULL || right == NULL || left->count != right->count || left->omitted_state != right->omitted_state) { return comparison; } comparison.comparable = 1u; for (index = 0u; index < left->count; ++index) { const CisProjectionField *left_field = &left->fields[index]; const CisProjectionField *right_field = &right->fields[index]; if (!name_equal(left_field->name, right_field->name) || left_field->source_state_index != right_field->source_state_index || left_field->multiplier != right_field->multiplier || left_field->offset != right_field->offset || left_field->kind != right_field->kind) { comparison.comparable = 0u; return comparison; } if (left->values[index] == right->values[index]) { ++equal; } } comparison.equivalent = equal == left->count; comparison.similarity_permyriad = left->count == 0u ? 10000u : (uint16_t)(((uint32_t)equal * 10000u) / left->count); return comparison; } static int event_symbol_equal(const CisEvent *left, const CisEvent *right, const uint8_t *participant_map, const uint8_t *action_map) { return participant_map[left->participant_index] == right->participant_index && action_map[left->action_index] == right->action_index && left->status == right->status && left->outcome == right->outcome; } CisComparison cis_compare_traces(const CisEvent *left, uint16_t left_count, const CisEvent *right, uint16_t right_count, const uint8_t *participant_map, uint8_t participant_map_count, const uint8_t *action_map, uint8_t action_map_count) { uint16_t previous[CIS_MAX_TRACE + 1u]; uint16_t current[CIS_MAX_TRACE + 1u]; CisComparison comparison = {0u, 0u, 0u}; uint16_t row; uint16_t column; uint16_t maximum; if ((left == NULL && left_count != 0u) || (right == NULL && right_count != 0u) || left_count > CIS_MAX_TRACE || right_count > CIS_MAX_TRACE || participant_map == NULL || action_map == NULL) { return comparison; } for (row = 0u; row < left_count; ++row) { if (left[row].participant_index >= participant_map_count || left[row].action_index >= action_map_count) { return comparison; } } comparison.comparable = 1u; for (column = 0u; column <= right_count; ++column) { previous[column] = column; } for (row = 1u; row <= left_count; ++row) { current[0] = row; for (column = 1u; column <= right_count; ++column) { uint16_t deletion = (uint16_t)(previous[column] + 1u); uint16_t insertion = (uint16_t)(current[column - 1u] + 1u); uint16_t substitution = (uint16_t)(previous[column - 1u] + (event_symbol_equal(&left[row - 1u], &right[column - 1u], participant_map, action_map) ? 0u : 1u)); uint16_t best = deletion < insertion ? deletion : insertion; current[column] = best < substitution ? best : substitution; } for (column = 0u; column <= right_count; ++column) { previous[column] = current[column]; } } maximum = left_count > right_count ? left_count : right_count; comparison.equivalent = previous[right_count] == 0u; comparison.similarity_permyriad = maximum == 0u ? 10000u : (uint16_t)(10000u - ((uint32_t)previous[right_count] * 10000u) / maximum); return comparison; } uint16_t cis_measure_action_frequency(const CisSystem *system, uint8_t action_index) { uint16_t count = 0u; uint16_t index; if (system == NULL || action_index >= system->domain.action_count) { return 0u; } for (index = 0u; index < system->trace_count; ++index) { if (system->trace[index].action_index == action_index && system->trace[index].status == CIS_EVENT_EXECUTED) { ++count; } } return count; } uint64_t cis_measure_elapsed(const CisSystem *system) { if (system == NULL || system->trace_count < 2u) { return 0u; } return system->trace[system->trace_count - 1u].tick - system->trace[0].tick; } uint8_t cis_measure_completion(const CisState *state, const CisPredicate *completion) { return (uint8_t)predicate_holds(state, completion); } CisResult cis_measure_recovery(const CisSystem *system, uint32_t after_sequence, const CisPredicate *recovered, uint64_t *ticks_out) { CisState current; uint16_t index; uint64_t start_tick; if (system == NULL || recovered == NULL || ticks_out == NULL || after_sequence >= system->trace_count || recovered->state_index >= system->initial_state.count) { return CIS_ERR_ARGUMENT; } current = system->initial_state; start_tick = system->trace[after_sequence].tick; for (index = 0u; index < system->trace_count; ++index) { const CisEvent *event = &system->trace[index]; if (cis_state_hash(¤t) != event->before_hash) { return CIS_ERR_REPLAY_DIVERGED; } if (event->status == CIS_EVENT_EXECUTED) { CisState next; if (event->action_index >= system->domain.action_count) { return CIS_ERR_REPLAY_DIVERGED; } if (apply_action(&system->domain, &system->domain.actions[event->action_index], ¤t, &next) != CIS_OK) { return CIS_ERR_REPLAY_DIVERGED; } current = next; } if (cis_state_hash(¤t) != event->after_hash) { return CIS_ERR_REPLAY_DIVERGED; } if (index > after_sequence && predicate_holds(¤t, recovered)) { *ticks_out = event->tick - start_tick; return CIS_OK; } } return CIS_ERR_NOT_FOUND; } uint16_t cis_measure_opportunity_mismatch(const CisOpportunity *opportunity) { uint8_t objectively_available; if (opportunity == NULL) { return 0u; } objectively_available = opportunity->domain_valid && opportunity->capable && opportunity->permitted && opportunity->enabled && opportunity->exposed; return objectively_available == opportunity->believed_available ? 0u : 10000u; } uint8_t cis_trace_has_aba_recurrence_pattern(const CisSystem *system) { uint16_t first; uint16_t second; uint16_t third; if (system == NULL) { return 0u; } for (first = 0u; first < system->trace_count; ++first) { if (system->trace[first].status != CIS_EVENT_EXECUTED || system->trace[first].before_hash == system->trace[first].after_hash) { continue; } for (second = (uint16_t)(first + 1u); second < system->trace_count; ++second) { if (system->trace[second].status != CIS_EVENT_EXECUTED || system->trace[second].before_hash == system->trace[second].after_hash || system->trace[second].participant_index == system->trace[first].participant_index) { continue; } for (third = (uint16_t)(second + 1u); third < system->trace_count; ++third) { if (system->trace[third].status == CIS_EVENT_EXECUTED && system->trace[third].before_hash != system->trace[third].after_hash && system->trace[third].participant_index == system->trace[first].participant_index) { return 1u; } } } } return 0u; } const char *cis_result_name(CisResult result) { switch (result) { case CIS_OK: return "ok"; case CIS_ERR_ARGUMENT: return "invalid argument"; case CIS_ERR_CAPACITY: return "capacity exhausted"; case CIS_ERR_DUPLICATE: return "duplicate identity"; case CIS_ERR_NOT_FOUND: return "not found"; case CIS_ERR_BOUNDS: return "state out of bounds"; case CIS_ERR_CAPABILITY: return "capability absent"; case CIS_ERR_PERMISSION: return "permission denied"; case CIS_ERR_DISABLED: return "precondition unsatisfied"; case CIS_ERR_INVARIANT: return "invariant violated"; case CIS_ERR_OVERFLOW: return "integer overflow"; case CIS_ERR_REPLAY_DIVERGED: return "replay diverged"; default: return "unknown result"; } } ======================================================================== ## FILE: app/tests/test_cis.c (270 lines, 11.7 KiB) ======================================================================== #include "cis.h" #include #define REQUIRE(expression) do { \ if (!(expression)) { \ printf("FAIL line %d: %s\n", __LINE__, #expression); \ return 1; \ } \ } while (0) enum { ROLE_USER = 0, ROLE_ADMIN = 1 }; enum { CAP_MOVE = 1u, CAP_LOCK = 2u }; typedef struct { CisDomain domain; uint8_t position; uint8_t locked; uint8_t open; uint8_t close; uint8_t lock; uint8_t unlock; uint8_t violate; } Fixture; static int build_fixture(Fixture *fixture) { CisAction action; cis_domain_init(&fixture->domain); REQUIRE(cis_domain_add_variable(&fixture->domain, "position", 0, 1, &fixture->position) == CIS_OK); REQUIRE(cis_domain_add_variable(&fixture->domain, "locked", 0, 1, &fixture->locked) == CIS_OK); REQUIRE(cis_domain_add_variable(&fixture->domain, "position", 0, 1, NULL) == CIS_ERR_DUPLICATE); cis_action_init(&action, "open"); action.required_capabilities = CAP_MOVE; action.permitted_roles = UINT32_C(1) << ROLE_USER; REQUIRE(cis_action_add_precondition(&action, (CisPredicate){fixture->position, CIS_PRED_EQ, 0}) == CIS_OK); REQUIRE(cis_action_add_precondition(&action, (CisPredicate){fixture->locked, CIS_PRED_EQ, 0}) == CIS_OK); REQUIRE(cis_action_add_effect(&action, (CisEffect){fixture->position, CIS_EFFECT_SET, 1}) == CIS_OK); action.reverse_action = 1; REQUIRE(cis_domain_add_action(&fixture->domain, &action, &fixture->open) == CIS_OK); cis_action_init(&action, "close"); action.required_capabilities = CAP_MOVE; action.permitted_roles = UINT32_C(1) << ROLE_USER; REQUIRE(cis_action_add_precondition(&action, (CisPredicate){fixture->position, CIS_PRED_EQ, 1}) == CIS_OK); REQUIRE(cis_action_add_effect(&action, (CisEffect){fixture->position, CIS_EFFECT_SET, 0}) == CIS_OK); action.reverse_action = 0; REQUIRE(cis_domain_add_action(&fixture->domain, &action, &fixture->close) == CIS_OK); cis_action_init(&action, "lock"); action.required_capabilities = CAP_LOCK; action.permitted_roles = UINT32_C(1) << ROLE_ADMIN; REQUIRE(cis_action_add_precondition(&action, (CisPredicate){fixture->position, CIS_PRED_EQ, 0}) == CIS_OK); REQUIRE(cis_action_add_effect(&action, (CisEffect){fixture->locked, CIS_EFFECT_SET, 1}) == CIS_OK); action.reverse_action = 3; REQUIRE(cis_domain_add_action(&fixture->domain, &action, &fixture->lock) == CIS_OK); cis_action_init(&action, "unlock"); action.required_capabilities = CAP_LOCK; action.permitted_roles = UINT32_C(1) << ROLE_ADMIN; REQUIRE(cis_action_add_effect(&action, (CisEffect){fixture->locked, CIS_EFFECT_SET, 0}) == CIS_OK); action.reverse_action = 2; REQUIRE(cis_domain_add_action(&fixture->domain, &action, &fixture->unlock) == CIS_OK); cis_action_init(&action, "violate bounds"); action.permitted_roles = UINT32_C(1) << ROLE_USER; REQUIRE(cis_action_add_effect(&action, (CisEffect){fixture->position, CIS_EFFECT_SET, 2}) == CIS_OK); REQUIRE(cis_domain_add_action(&fixture->domain, &action, &fixture->violate) == CIS_OK); REQUIRE(cis_domain_add_invariant(&fixture->domain, (CisPredicate){fixture->locked, CIS_PRED_GE, 0}) == CIS_OK); return 0; } static int test_execution_replay_and_interaction(const Fixture *fixture) { CisSystem system; CisState initial = {{0}, 2}; CisState replayed; uint8_t alice; uint8_t bob; uint8_t admin; uint64_t recovery_ticks; CisPredicate recovered = {fixture->position, CIS_PRED_EQ, 1}; REQUIRE(cis_system_init(&system, &fixture->domain, &initial) == CIS_OK); REQUIRE(cis_system_add_participant(&system, "alice", ROLE_USER, CAP_MOVE, &alice) == CIS_OK); REQUIRE(cis_system_add_participant(&system, "bob", ROLE_USER, CAP_MOVE, &bob) == CIS_OK); REQUIRE(cis_system_add_participant(&system, "root", ROLE_ADMIN, CAP_MOVE | CAP_LOCK, &admin) == CIS_OK); REQUIRE(cis_execute(&system, alice, fixture->lock, 1) == CIS_ERR_CAPABILITY); REQUIRE(cis_execute(&system, admin, fixture->open, 2) == CIS_ERR_PERMISSION); REQUIRE(cis_execute(&system, alice, fixture->open, 3) == CIS_OK); REQUIRE(cis_record_outcome(&system, 2, CIS_OUTCOME_SUCCESS) == CIS_OK); REQUIRE(cis_record_outcome(&system, 2, CIS_OUTCOME_SUCCESS) == CIS_ERR_DUPLICATE); REQUIRE(cis_execute(&system, alice, fixture->open, 4) == CIS_ERR_DISABLED); REQUIRE(cis_execute(&system, bob, fixture->close, 5) == CIS_OK); REQUIRE(cis_execute(&system, alice, fixture->open, 6) == CIS_OK); REQUIRE(cis_execute(&system, alice, fixture->violate, 7) == CIS_ERR_BOUNDS); REQUIRE(cis_execute(&system, admin, fixture->lock, 6) == CIS_ERR_ARGUMENT); REQUIRE(system.state.values[fixture->position] == 1); REQUIRE(system.trace_count == 7); REQUIRE(cis_trace_has_aba_recurrence_pattern(&system) == 1); REQUIRE(cis_measure_action_frequency(&system, fixture->open) == 2); REQUIRE(cis_measure_elapsed(&system) == 6); REQUIRE(cis_measure_recovery(&system, 4, &recovered, &recovery_ticks) == CIS_OK); REQUIRE(recovery_ticks == 1); REQUIRE(cis_replay(&system, &replayed) == CIS_OK); REQUIRE(cis_state_hash(&replayed) == cis_state_hash(&system.state)); REQUIRE(system.trace[0].schema_version == CIS_TRACE_SCHEMA_VERSION); system.trace[2].after_hash ^= UINT64_C(1); REQUIRE(cis_replay(&system, &replayed) == CIS_ERR_REPLAY_DIVERGED); return 0; } static int test_projection_and_opportunity(const Fixture *fixture) { CisSystem system; CisState initial = {{0}, 2}; CisProjection projection; CisProjectedState first; CisProjectedState second; CisProjectedState incompatible; CisProjection other_projection; CisOpportunity opportunity; CisPredicate target = {fixture->position, CIS_PRED_EQ, 1}; uint8_t alice; uint8_t reachable; CisComparison comparison; REQUIRE(cis_system_init(&system, &fixture->domain, &initial) == CIS_OK); REQUIRE(cis_system_add_participant(&system, "alice", ROLE_USER, CAP_MOVE, &alice) == CIS_OK); cis_projection_init(&projection); projection.exposed_actions = UINT32_C(1) << fixture->open; projection.signaled_actions = UINT32_C(1) << fixture->open; REQUIRE(cis_projection_add_field(&projection, "door", fixture->position, 1, 0, CIS_FIELD_PRESERVED) == CIS_OK); REQUIRE(cis_projection_add_field(&projection, "constant", -1, 0, 7, CIS_FIELD_INTRODUCED) == CIS_OK); REQUIRE(cis_project(&projection, &system.state, &first) == CIS_OK); REQUIRE(first.values[0] == 0 && first.values[1] == 7); REQUIRE(first.omitted_state == (UINT32_C(1) << fixture->locked)); REQUIRE(cis_reachable(&fixture->domain, &system.state, &target, ROLE_USER, CAP_MOVE, 1, &reachable) == CIS_OK); REQUIRE(reachable == 1); REQUIRE(cis_opportunity(&system, &projection, alice, fixture->open, 0, 7000, 1, 500, &target, 1, &opportunity) == CIS_OK); REQUIRE(opportunity.domain_valid && opportunity.capable && opportunity.permitted && opportunity.enabled && opportunity.reachable && opportunity.exposed && opportunity.signaled && opportunity.reversible); REQUIRE(!opportunity.selected && !opportunity.executed); REQUIRE(cis_measure_opportunity_mismatch(&opportunity) == 10000); REQUIRE(cis_execute(&system, alice, fixture->open, 10) == CIS_OK); REQUIRE(cis_record_outcome(&system, 0, CIS_OUTCOME_SUCCESS) == CIS_OK); REQUIRE(cis_project(&projection, &system.state, &second) == CIS_OK); comparison = cis_compare_projections(&first, &second); REQUIRE(comparison.comparable && !comparison.equivalent); REQUIRE(comparison.similarity_permyriad == 5000); cis_projection_init(&other_projection); REQUIRE(cis_projection_add_field(&other_projection, "different meaning", fixture->position, 1, 0, CIS_FIELD_PRESERVED) == CIS_OK); REQUIRE(cis_projection_add_field(&other_projection, "constant", -1, 0, 7, CIS_FIELD_INTRODUCED) == CIS_OK); REQUIRE(cis_project(&other_projection, &system.state, &incompatible) == CIS_OK); comparison = cis_compare_projections(&second, &incompatible); REQUIRE(!comparison.comparable); REQUIRE(cis_opportunity(&system, &projection, alice, fixture->open, 1, 10000, 1, 0, &target, 0, &opportunity) == CIS_OK); REQUIRE(opportunity.selected && opportunity.executed && opportunity.successful && !opportunity.enabled); return 0; } static int test_comparison_and_measurement(const Fixture *fixture) { CisState closed = {{0, 0}, 2}; CisState open = {{1, 0}, 2}; CisPredicate completion = {fixture->position, CIS_PRED_EQ, 1}; CisComparison states; CisEvent left[2] = {{0}}; CisEvent right[2] = {{0}}; CisComparison traces; uint8_t participant_map[2] = {0, 1}; uint8_t action_map[CIS_MAX_ACTIONS]; uint8_t index; for (index = 0u; index < CIS_MAX_ACTIONS; ++index) { action_map[index] = index; } REQUIRE(cis_state_hash(&closed) == UINT64_C(16981056525137609861)); REQUIRE(cis_state_hash(&open) == UINT64_C(11289045597036932164)); states = cis_compare_states(&fixture->domain, &closed, &open); REQUIRE(states.comparable && !states.equivalent); REQUIRE(states.similarity_permyriad == 5000); REQUIRE(cis_measure_completion(&open, &completion) == 1); REQUIRE(cis_measure_completion(&closed, &completion) == 0); left[0].participant_index = 0; left[0].action_index = fixture->open; left[0].status = CIS_EVENT_EXECUTED; left[1].participant_index = 1; left[1].action_index = fixture->close; left[1].status = CIS_EVENT_EXECUTED; right[0] = left[0]; right[1] = left[1]; traces = cis_compare_traces(left, 2, right, 2, participant_map, 2, action_map, CIS_MAX_ACTIONS); REQUIRE(traces.comparable && traces.equivalent && traces.similarity_permyriad == 10000); right[0].participant_index = 1; right[1].participant_index = 0; participant_map[0] = 1; participant_map[1] = 0; traces = cis_compare_traces(left, 2, right, 2, participant_map, 2, action_map, CIS_MAX_ACTIONS); REQUIRE(traces.comparable && traces.equivalent); traces = cis_compare_traces(left, 2, right, 2, NULL, 0, action_map, CIS_MAX_ACTIONS); REQUIRE(!traces.comparable); right[0].participant_index = 0; right[1].participant_index = 1; participant_map[0] = 0; participant_map[1] = 1; right[1].action_index = fixture->open; traces = cis_compare_traces(left, 2, right, 2, participant_map, 2, action_map, CIS_MAX_ACTIONS); REQUIRE(traces.comparable && !traces.equivalent && traces.similarity_permyriad == 5000); return 0; } int main(void) { Fixture fixture; REQUIRE(build_fixture(&fixture) == 0); REQUIRE(test_execution_replay_and_interaction(&fixture) == 0); REQUIRE(test_projection_and_opportunity(&fixture) == 0); REQUIRE(test_comparison_and_measurement(&fixture) == 0); printf("PASS: fundamental CIS substrate\n"); return 0; } ======================================================================== ## FILE: app/tests/test_examples.c (118 lines, 3.8 KiB) ======================================================================== #include #include #define SOURCE_CAPACITY 32768u #define ESCAPED_CAPACITY 131072u #define RENDERED_CAPACITY 131072u static char source[SOURCE_CAPACITY]; static char escaped[ESCAPED_CAPACITY]; static char rendered[RENDERED_CAPACITY]; static int read_file(const char *path, char *buffer, size_t capacity, size_t *length_out) { FILE *file = fopen(path, "rb"); size_t length; if (file == NULL) { return 0; } length = fread(buffer, 1u, capacity - 1u, file); if (ferror(file) || !feof(file)) { fclose(file); return 0; } fclose(file); buffer[length] = '\0'; *length_out = length; return 1; } static int append_text(char *target, size_t capacity, size_t *length, const char *text) { size_t index = 0u; while (text[index] != '\0') { if (*length + 1u >= capacity) { return 0; } target[(*length)++] = text[index++]; } return 1; } static int html_escape(const char *input, size_t input_length, char *output, size_t capacity) { size_t input_index; size_t output_length = 0u; for (input_index = 0u; input_index < input_length; ++input_index) { const char *replacement = NULL; char literal[2] = {input[input_index], '\0'}; switch (input[input_index]) { case '&': replacement = "&"; break; case '<': replacement = "<"; break; case '>': replacement = ">"; break; case '"': replacement = """; break; case '\'': replacement = "'"; break; default: replacement = literal; break; } if (!append_text(output, capacity, &output_length, replacement)) { return 0; } } output[output_length] = '\0'; return 1; } static int verify_pair(const char *source_path, const char *rendered_path) { size_t source_length; size_t rendered_length; if (!read_file(source_path, source, sizeof(source), &source_length) || !read_file(rendered_path, rendered, sizeof(rendered), &rendered_length) || rendered_length == 0u || !html_escape(source, source_length, escaped, sizeof(escaped)) || strstr(rendered, escaped) == NULL) { return 0; } return 1; } static int verify_interaction_claim_boundaries(void) { size_t source_length; if (!read_file( "examples/visualizations/src/interaction-substrate-lab.html", source, sizeof(source), &source_length)) { return 0; } return source_length > 0u && strstr(source, "const systemExecutable = current.domain && current.capable && current.permitted && current.enabled;") != NULL && strstr(source, "const projectedAvailable = systemExecutable && current.exposed;") != NULL && strstr(source, "event.executed && event.outcome === 'failure') ? false : null") != NULL && strstr(source, "Participant belief matches projected availability") != NULL; } int main(void) { if (!verify_pair( "examples/visualizations/src/interaction-substrate-lab.html", "examples/visualizations/interaction-substrate-lab.html") || !verify_pair( "examples/visualizations/src/projection-invariance-workbench.html", "examples/visualizations/projection-invariance-workbench.html") || !verify_pair( "examples/visualizations/src/evidence-inference-ladder.html", "examples/visualizations/evidence-inference-ladder.html") || !verify_interaction_claim_boundaries()) { puts("FAIL: identified standalone output is missing or stale"); return 1; } puts("PASS: identified example sources and generated output"); return 0; } ======================================================================== ## FILE: app/tests/test_schemas.c (366 lines, 15.8 KiB) ======================================================================== #include #include #include #define SCHEMA_CAPACITY 131072u #define PATH_CAPACITY 512u static char schema_text[SCHEMA_CAPACITY]; static const char *cursor; static const char *limit; static char current_directory[PATH_CAPACITY]; static int parse_error; static void skip_space(void) { while (cursor < limit && isspace((unsigned char)*cursor)) { ++cursor; } } static int parse_string(char *output, size_t capacity) { size_t length = 0u; if (cursor >= limit || *cursor++ != '"') return 0; while (cursor < limit && *cursor != '"') { char value = *cursor++; if ((unsigned char)value < 0x20u) return 0; if (value == '\\') { if (cursor >= limit) return 0; value = *cursor++; if (value == 'u') { unsigned index; for (index = 0u; index < 4u; ++index) { if (cursor >= limit || !isxdigit((unsigned char)*cursor++)) { return 0; } } value = '?'; } else if (strchr("\"\\/bfnrt", value) == NULL) { return 0; } } if (output != NULL && length + 1u < capacity) output[length] = value; ++length; } if (cursor >= limit || *cursor++ != '"') return 0; if (output != NULL) { if (length >= capacity) return 0; output[length] = '\0'; } return 1; } static int reference_exists(const char *reference) { char path[PATH_CAPACITY]; size_t directory_length; size_t reference_length = 0u; FILE *file; if (reference[0] == '#' || strstr(reference, "://") != NULL) return 1; while (reference[reference_length] != '\0' && reference[reference_length] != '#') { ++reference_length; } directory_length = strlen(current_directory); if (directory_length + reference_length + 1u >= sizeof(path)) return 0; memcpy(path, current_directory, directory_length); memcpy(path + directory_length, reference, reference_length); path[directory_length + reference_length] = '\0'; file = fopen(path, "rb"); if (file == NULL) return 0; fclose(file); return 1; } static void parse_value(void); static void parse_array(void) { ++cursor; skip_space(); if (cursor < limit && *cursor == ']') { ++cursor; return; } while (!parse_error) { parse_value(); skip_space(); if (cursor < limit && *cursor == ']') { ++cursor; return; } if (cursor >= limit || *cursor++ != ',') { parse_error = 1; return; } skip_space(); } } static void parse_object(void) { char key[128]; ++cursor; skip_space(); if (cursor < limit && *cursor == '}') { ++cursor; return; } while (!parse_error) { if (!parse_string(key, sizeof(key))) { parse_error = 1; return; } skip_space(); if (cursor >= limit || *cursor++ != ':') { parse_error = 1; return; } skip_space(); if (strcmp(key, "$ref") == 0) { char reference[PATH_CAPACITY]; if (!parse_string(reference, sizeof(reference)) || !reference_exists(reference)) { parse_error = 1; return; } } else { parse_value(); } skip_space(); if (cursor < limit && *cursor == '}') { ++cursor; return; } if (cursor >= limit || *cursor++ != ',') { parse_error = 1; return; } skip_space(); } } static void parse_number(void) { if (cursor < limit && *cursor == '-') ++cursor; if (cursor >= limit || !isdigit((unsigned char)*cursor)) { parse_error = 1; return; } if (*cursor == '0') ++cursor; else while (cursor < limit && isdigit((unsigned char)*cursor)) ++cursor; if (cursor < limit && *cursor == '.') { ++cursor; if (cursor >= limit || !isdigit((unsigned char)*cursor)) { parse_error = 1; return; } while (cursor < limit && isdigit((unsigned char)*cursor)) ++cursor; } if (cursor < limit && (*cursor == 'e' || *cursor == 'E')) { ++cursor; if (cursor < limit && (*cursor == '+' || *cursor == '-')) ++cursor; if (cursor >= limit || !isdigit((unsigned char)*cursor)) { parse_error = 1; return; } while (cursor < limit && isdigit((unsigned char)*cursor)) ++cursor; } } static void parse_value(void) { skip_space(); if (cursor >= limit) { parse_error = 1; return; } if (*cursor == '{') parse_object(); else if (*cursor == '[') parse_array(); else if (*cursor == '"') { if (!parse_string(NULL, 0u)) parse_error = 1; } else if (*cursor == '-' || isdigit((unsigned char)*cursor)) parse_number(); else if ((size_t)(limit - cursor) >= 4u && strncmp(cursor, "true", 4u) == 0) cursor += 4; else if ((size_t)(limit - cursor) >= 5u && strncmp(cursor, "false", 5u) == 0) cursor += 5; else if ((size_t)(limit - cursor) >= 4u && strncmp(cursor, "null", 4u) == 0) cursor += 4; else parse_error = 1; } static int validate_json(const char *path, int require_schema_declaration) { FILE *file = fopen(path, "rb"); size_t length; const char *slash; if (file == NULL) return 0; length = fread(schema_text, 1u, sizeof(schema_text) - 1u, file); if (ferror(file) || !feof(file)) { fclose(file); return 0; } fclose(file); schema_text[length] = '\0'; if (require_schema_declaration && strstr(schema_text, "\"$schema\": \"https://json-schema.org/draft/2020-12/schema\"") == NULL) { return 0; } slash = strrchr(path, '/'); if (slash == NULL || (size_t)(slash - path + 2) > sizeof(current_directory)) { return 0; } memcpy(current_directory, path, (size_t)(slash - path + 1)); current_directory[slash - path + 1] = '\0'; cursor = schema_text; limit = schema_text + length; parse_error = 0; parse_value(); skip_space(); return !parse_error && cursor == limit; } static int contains_all_keys(const char *const *keys, size_t count) { size_t index; for (index = 0u; index < count; ++index) { if (strstr(schema_text, keys[index]) == NULL) return 0; } return 1; } static int validate_contract_instance(const char *path, const char *const *specific_keys, size_t specific_count) { static const char *common_keys[] = { "\"contract_id\"", "\"schema_version\": \"0.2.0\"", "\"contract_version\": \"0.2.0\"", "\"theory_version\"", "\"status\"", "\"authority\"", "\"construct_refs\"", "\"scope\"", "\"prohibited_interpretations\"", "\"identifier_status\": \"unratified\"", "\"canonical_id\": null" }; return validate_json(path, 0) && contains_all_keys(common_keys, sizeof(common_keys) / sizeof(common_keys[0])) && contains_all_keys(specific_keys, specific_count); } static int validate_study_fixture(const char *path, int expected_complete) { static const char *required_keys[] = { "\"study_id\"", "\"schema_version\"", "\"study_version\"", "\"theory_version\"", "\"protocol_ref\"", "\"contract_refs\"", "\"scope\"", "\"construct_refs\"", "\"participants\"", "\"environments\"", "\"interaction_episodes\"", "\"states\"", "\"records\"", "\"coded_events\"", "\"behavioral_traces\"", "\"measures\"", "\"uncertainties\"" }; int complete; if (!validate_json(path, 0)) return 0; complete = contains_all_keys(required_keys, sizeof(required_keys) / sizeof(required_keys[0])); return complete == expected_complete; } int main(void) { static const char *files[] = { "../docs/04_Reference/Templates/Contract_Common.schema.json", "../docs/04_Reference/Templates/Projection_Contract.schema.json", "../docs/04_Reference/Templates/Opportunity_Contract.schema.json", "../docs/04_Reference/Templates/Interaction_Contract.schema.json", "../docs/04_Reference/Templates/Behavioral_Evidence_Contract.schema.json", "../docs/04_Reference/Templates/Measurement_Contract.schema.json", "../docs/04_Reference/Templates/Similarity_Contract.schema.json", "../docs/04_Reference/Templates/Transfer_Contract.schema.json", "../docs/04_Reference/Templates/Strategy_Contract.schema.json", "../docs/04_Reference/Templates/Prediction_Contract.schema.json", "../docs/04_Reference/Templates/Comparison_Contract.schema.json", "../docs/04_Reference/Dataset_Schema/interaction_study.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/common.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/participant.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/environment.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/interaction-episode.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/interaction-contract.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/projection-contract.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/measurement-contract.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/raw-record.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/coded-event.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/behavioral-trace.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/opportunity-profile.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/measure.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/uncertainty.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/similarity-profile.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/transfer-record.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/strategy-hypothesis.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/prediction-record.schema.json", "../docs/04_Reference/Dataset_Schema/schemas/comparison-profile.schema.json", "../docs/01_Knowledge_System_of_Record/10_Governance/consent-record.schema.json" }; static const char *projection_keys[] = { "\"target_ref\"", "\"target_host\"", "\"modality\"", "\"mapping_rule\"", "\"interpretation_assumptions\"", "\"preserved_properties\"", "\"transformed_properties\"", "\"omitted_properties\"", "\"introduced_properties\"", "\"exposed_operations\"", "\"signifiers\"", "\"feedback_channels\"", "\"observer_class\"", "\"intended_use\"", "\"tolerances\"", "\"uncertainty_refs\"", "\"failure_conditions\"" }; static const char *opportunity_keys[] = { "\"system_ref\"", "\"participant_ref\"", "\"action_ref\"", "\"action_vocabulary_ref\"", "\"projection_ref\"", "\"task_ref\"", "\"authority_ref\"", "\"state_ref\"", "\"time_basis\"", "\"relation_definitions\"", "\"domain_valid\"", "\"capable\"", "\"permitted\"", "\"enabled\"", "\"reachable\"", "\"exposed\"", "\"signaled\"", "\"believed_available\"", "\"selected\"", "\"executed\"", "\"successful\"", "\"reversible\"", "\"evidence_requirements\"", "\"expected_consequence_definition\"", "\"recovery_definition\"", "\"uncertainty_requirements\"" }; static const char *interaction_keys[] = { "\"participant_refs\"", "\"environment_refs\"", "\"boundary\"", "\"timescale\"", "\"initiation_conditions\"", "\"initial_state_ref\"", "\"coupling_relations\"", "\"preconditions\"", "\"perturbation_conditions\"", "\"uptake_conditions\"", "\"postconditions\"", "\"event_types\"", "\"transition_semantics_ref\"", "\"protocol\"", "\"invariants\"", "\"evidence_requirements\"", "\"failure_conditions\"", "\"recovery_conditions\"", "\"completion_conditions\"", "\"episode_identity_rule\"", "\"provenance_requirements\"", "\"uncertainty_assumptions\"" }; static const char *behavioral_keys[] = { "\"raw_source_refs\"", "\"instrument_refs\"", "\"observation_model\"", "\"detection_rules\"", "\"event_coding_rules\"", "\"segmentation_rules\"", "\"attribution_rules\"", "\"ordering_rule\"", "\"missingness_rules\"", "\"alternative_explanations\"", "\"uncertainty_model_ref\"", "\"falsifying_evidence\"", "\"claim_limits\"", "\"review_requirements\"", "\"evidence_lineage_rule\"", "\"provenance_requirements\"" }; static const char *measurement_keys[] = { "\"measurand\"", "\"unit\"", "\"level_of_analysis\"", "\"observation_model\"", "\"instrument_ref\"", "\"operationalization\"", "\"coding_rules\"", "\"estimator\"", "\"scale_type\"", "\"permissible_transformations\"", "\"permissible_comparisons\"", "\"permitted_interpretations\"", "\"uncertainty_model_ref\"", "\"uncertainty_budget\"", "\"reliability_evidence_requirements\"", "\"validity_evidence_requirements\"", "\"comparison_scope\"", "\"missingness_rules\"" }; struct InstanceSpec { const char *path; const char *const *specific_keys; size_t specific_count; }; static const struct InstanceSpec instances[] = { { "examples/studies/CIS-EX-008/contracts/projection-signaled.json", projection_keys, sizeof(projection_keys) / sizeof(projection_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/projection-unsignaled.json", projection_keys, sizeof(projection_keys) / sizeof(projection_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/opportunity.json", opportunity_keys, sizeof(opportunity_keys) / sizeof(opportunity_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/interaction.json", interaction_keys, sizeof(interaction_keys) / sizeof(interaction_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/behavioral-evidence.json", behavioral_keys, sizeof(behavioral_keys) / sizeof(behavioral_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/measurement-discovery.json", measurement_keys, sizeof(measurement_keys) / sizeof(measurement_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/measurement-invalid-attempt.json", measurement_keys, sizeof(measurement_keys) / sizeof(measurement_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/measurement-recovery.json", measurement_keys, sizeof(measurement_keys) / sizeof(measurement_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/measurement-completion.json", measurement_keys, sizeof(measurement_keys) / sizeof(measurement_keys[0]) }, { "examples/studies/CIS-EX-008/contracts/measurement-belief.json", measurement_keys, sizeof(measurement_keys) / sizeof(measurement_keys[0]) } }; size_t index; for (index = 0u; index < sizeof(files) / sizeof(files[0]); ++index) { if (!validate_json(files[index], 1)) { printf("FAIL schema: %s\n", files[index]); return 1; } } for (index = 0u; index < sizeof(instances) / sizeof(instances[0]); ++index) { if (!validate_contract_instance(instances[index].path, instances[index].specific_keys, instances[index].specific_count)) { printf("FAIL contract instance: %s\n", instances[index].path); return 1; } } if (!validate_study_fixture( "examples/studies/CIS-EX-008/data/valid-synthetic-study.json", 1) || !validate_study_fixture( "examples/studies/CIS-EX-008/data/invalid-missing-environment.json", 0)) { puts("FAIL study dataset fixtures"); return 1; } printf("PASS: %u JSON schemas and local references; %u identified contract instances; valid/invalid study fixtures\n", (unsigned)(sizeof(files) / sizeof(files[0])), (unsigned)index); return 0; } ======================================================================== ## FILE: app/tests/test_stress.c (145 lines, 5.1 KiB) ======================================================================== #include "cis.h" #include #define CHECK(expression) do { \ if (!(expression)) { \ printf("FAIL line %d: %s\n", __LINE__, #expression); \ return 1; \ } \ } while (0) static uint32_t random_word(uint32_t *state) { uint32_t value = *state; value ^= value << 13u; value ^= value >> 17u; value ^= value << 5u; *state = value; return value; } static int build_counter(CisDomain *domain, uint8_t *counter, uint8_t *increment, uint8_t *decrement) { CisAction action; cis_domain_init(domain); CHECK(cis_domain_add_variable(domain, "counter", -8, 8, counter) == CIS_OK); cis_action_init(&action, "increment"); action.required_capabilities = 1u; action.permitted_roles = 1u; CHECK(cis_action_add_effect(&action, (CisEffect){*counter, CIS_EFFECT_ADD, 1}) == CIS_OK); CHECK(cis_domain_add_action(domain, &action, increment) == CIS_OK); cis_action_init(&action, "decrement"); action.required_capabilities = 1u; action.permitted_roles = 1u; CHECK(cis_action_add_effect(&action, (CisEffect){*counter, CIS_EFFECT_ADD, -1}) == CIS_OK); CHECK(cis_domain_add_action(domain, &action, decrement) == CIS_OK); return 0; } static int test_deterministic_stress(void) { CisDomain domain; uint8_t counter; uint8_t increment; uint8_t decrement; uint32_t seed; CHECK(build_counter(&domain, &counter, &increment, &decrement) == 0); for (seed = 1u; seed <= 64u; ++seed) { CisState initial = {{0}, 1}; CisSystem system; CisState replayed; uint8_t participant; uint32_t random_state = seed; uint16_t step; int64_t expected = 0; CHECK(cis_system_init(&system, &domain, &initial) == CIS_OK); CHECK(cis_system_add_participant(&system, "actor", 0, 1u, &participant) == CIS_OK); for (step = 0u; step < CIS_MAX_TRACE; ++step) { uint8_t action = (random_word(&random_state) & 1u) != 0u ? increment : decrement; CisResult result = cis_execute(&system, participant, action, step); int64_t next = expected + (action == increment ? 1 : -1); if (next < -8 || next > 8) { CHECK(result == CIS_ERR_BOUNDS); } else { CHECK(result == CIS_OK); expected = next; CHECK(cis_record_outcome(&system, step, (random_word(&random_state) & 1u) != 0u ? CIS_OUTCOME_SUCCESS : CIS_OUTCOME_FAILURE) == CIS_OK); } CHECK(system.state.values[counter] == expected); CHECK(cis_replay(&system, &replayed) == CIS_OK); CHECK(replayed.values[counter] == expected); } CHECK(cis_execute(&system, participant, increment, CIS_MAX_TRACE) == CIS_ERR_CAPACITY); } return 0; } static int test_opportunity_independence(void) { CisDomain domain; CisAction action; CisState initial = {{0}, 1}; CisSystem system; CisProjection projection; CisOpportunity profile; CisPredicate target; uint8_t cell; uint8_t act; uint8_t capable; uint8_t incapable; cis_domain_init(&domain); CHECK(cis_domain_add_variable(&domain, "cell", 0, 1, &cell) == CIS_OK); cis_action_init(&action, "set"); action.required_capabilities = 1u; action.permitted_roles = 1u; CHECK(cis_action_add_precondition(&action, (CisPredicate){cell, CIS_PRED_EQ, 0}) == CIS_OK); CHECK(cis_action_add_effect(&action, (CisEffect){cell, CIS_EFFECT_SET, 1}) == CIS_OK); CHECK(cis_domain_add_action(&domain, &action, &act) == CIS_OK); CHECK(cis_system_init(&system, &domain, &initial) == CIS_OK); CHECK(cis_system_add_participant(&system, "capable", 0, 1u, &capable) == CIS_OK); CHECK(cis_system_add_participant(&system, "incapable", 0, 0u, &incapable) == CIS_OK); cis_projection_init(&projection); projection.signaled_actions = UINT32_C(1) << act; target = (CisPredicate){cell, CIS_PRED_EQ, 1}; CHECK(cis_opportunity(&system, &projection, capable, act, 1, 9000, 1, 100, &target, 1, &profile) == CIS_OK); CHECK(profile.capable && profile.permitted && profile.enabled && profile.reachable && !profile.exposed && profile.signaled && profile.believed_available); CHECK(cis_measure_opportunity_mismatch(&profile) == 10000u); projection.exposed_actions = UINT32_C(1) << act; projection.signaled_actions = 0u; CHECK(cis_opportunity(&system, &projection, incapable, act, 0, 10000, 0, 0, &target, 1, &profile) == CIS_OK); CHECK(!profile.capable && profile.permitted && profile.enabled && !profile.reachable && profile.exposed && !profile.signaled && !profile.believed_available); return 0; } int main(void) { CHECK(test_deterministic_stress() == 0); CHECK(test_opportunity_independence() == 0); printf("PASS: 8192 deterministic traces and opportunity independence\n"); return 0; } ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/01_Ontology/Current/A_Relational_Ontology_of_Computational_Interaction_v0.3.md (236 lines, 11.1 KiB) ======================================================================== # A Relational Ontology of Computational Interaction **Version:** Draft 0.3 **Status:** Provisional Foundational Model **Supersedes:** *A Relational Ontology of Computational Interaction*, Draft 0.2 and *A Canonical Ontology of Interaction*, Draft 0.1 ## Abstract Computational interaction is modeled as a recursive relational system rather than a linear user-interface pipeline. The current ontology incorporates the completed work on representation, scoped invariance, opportunity, interaction, behavior, measurement, similarity, and strategy. Interaction is not a primitive substance. A strict interaction episode is a bounded interval of reciprocal or recurrent constraint among distinguishable systems through coupling. Behavior is an attributed trajectory under an observation model. Measurement governs how observations become variables and claims. Similarity is typed rather than universal. Strategy is an inferred organization across contingencies rather than an observed sequence. The ontology coordinates established concepts and reusable contracts. It does not claim metaphysical universality, direct access to cognition, or disciplinary autonomy for Foundations of Computational Interaction (FCI). ## 1. Explanatory target The primary target is **computational interaction**: interaction in which computation participates in the phenomenon, mediates the relation among participants, or supplies the formal and empirical means of observation. A strict **interaction episode** is: > A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale. The reciprocal effect may be direct, asymmetric, delayed, probabilistic, or mediated by an environment. A one-way isolated causal effect is not sufficient under the strict definition. ## 2. Core ontological roles ### 2.1 Interaction participant — A A bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role. Participation does not imply autonomy, intelligence, consciousness, or learning. **Agent** is a subtype: an acting participant with an action-selection organization. ### 2.2 Domain commitments — O The entities, relations, identity conditions, modalities, constraints, and operation vocabulary admitted by the model or inquiry. ### 2.3 State — X The current physical, computational, social, or modeled condition of participants and environment. ### 2.4 Semantic assignment — S The rules assigning denotation, content, truth conditions, inferential consequences, or operational behavior to expressions, states, relations, or operations. ### 2.5 Projection — P A declared transformation from selected state or semantic relations into an accessible representation. Its contract declares preservation, transformation, omission, introduction, operations, assumptions, uncertainty, tolerance, and failure. ### 2.6 Representation — R The realized vehicle through which selected aspects of a target become accessible. Representation may introduce ordering, grouping, geometry, salience, modality, latency, ambiguity, and operations. ### 2.7 Interpretation — J The contextual application, recovery, construction, negotiation, or revision of significance by an interpreting participant or practice. ### 2.8 Opportunity profile — Ω A typed profile of domain validity, capability, permission, enablement, reachability, exposure, signaling, believed availability, expected consequence, reversibility, uncertainty, and associated trace predicates. Opportunity is a coordination framework, not a primitive. ### 2.9 Coupling — C A pathway through which a participant or shared medium changes another participant's transition structure, probabilities, timing, or reachable states. ### 2.10 Interaction episode — I A bounded coupled process containing perturbation, uptake, response, and sufficient recurrence or closure for identity. ### 2.11 Behavior — B A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model. ### 2.12 Trace — Tr A temporally ordered or partially ordered record of observable or attributed events. A trace supports behavioral inference but is not identical with behavior, action, policy, strategy, or mechanism. ### 2.13 Measurement — M The declared relation by which observations become variables, estimates, constructs, and comparisons. Every measurement requires a measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, and permitted interpretation. ### 2.14 Similarity and equivalence — K Typed comparison relations over tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements. The canonical output is a typed profile, not a universal scalar. ### 2.15 Strategy — Σ An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response across a declared class of states. Strategy is latent and requires rival discrimination. ### 2.16 Evidence — E A provenance-preserving chain connecting records, detection, attribution, measurement, latent interpretation, uncertainty, alternatives, falsifying evidence, and bounded claims. ## 3. Relational architecture ```text Domain commitments O ↔ State X ↔ Semantic assignment S ↕ Projection P ↓ Representation R ↕ Interpretation J ↕ Opportunity profile Ω ↕ Coupling C ↓ Interaction episode I ↓ Behavior B ↓ Trace Tr ↓ Measurement M ↓ Similarity / equivalence K ↕ Strategy Σ ↺ feedback, learning, revision ``` This is a dependency and evidence architecture, not a universal causal pipeline. Strategy and transfer can constrain later interpretation and opportunity; interaction changes state; measurement and comparison depend on declared observation models; interpretation may revise effective semantics. ## 4. Formal scaffolds An interaction type may be represented as: ```text I = ``` where participants, state, coupling topology, event set, transition kernel, recurrence relation, boundary/timescale, and closure/invariants are declared. A strategy contract may be represented as: ```text Σ = ``` where the components declare domain, state, observation, state abstraction, criteria, action repertoire, selection policy, information policy, commitments, recovery, switching, stopping, resources, and uncertainty. A similarity contract may be represented as: ```text K = ``` where target type, comparison frame, correspondence mapping, observables, admissible transformations, typed distances, weights, tolerances, uncertainty, and validity domain are declared. These tuples are analytical contracts, not claims that human cognition literally implements them. ## 5. Contract stack The research program now uses a coordinated contract stack: ```text Projection Contract what a representation preserves, transforms, omits, and introduces Opportunity Contract what actions are possible, permitted, enabled, exposed, signaled, believed, and recoverable Interaction Contract what episode exists, where its boundary lies, and how coupling and closure occur Behavioral Evidence Contract what records, events, attribution, traces, and claims are warranted Measurement Contract how observations become variables, estimates, constructs, and comparisons Similarity Contract how two targets may be identical, equivalent, similar, unknown, or incomparable Strategy Contract how conditional behavioral organization is represented and tested against rivals ``` Each contract has a different source of truth. They must not be collapsed into one schema. ## 6. Identity and comparison Token identity is historical identity of one bounded episode. Type identity is membership in an abstraction-defined class. Equivalence is exact preservation under a declared contract. Similarity is graded proximity under specified metrics and tolerances. Incomparability is the failure to establish a defensible common space. Semantic equivalence does not imply opportunity equivalence. Opportunity equivalence does not imply behavioral equivalence. Behavioral equivalence does not imply strategy or causal equivalence. Outcome equivalence does not establish process equivalence. ## 7. Evidence discipline The minimum evidence progression is: ```text raw record → verified event → episode trace → descriptive regularity → measured variable → candidate latent organization → rival discrimination → transfer or adaptation support → causal support → mechanistic or formal support ``` Claims may stop at any warranted level. They must not skip levels. ## 8. Participant history and context Language, skill, training, conventions, prior outcomes, tools, practices, goals, accessibility, and current constraints may alter interpretation, believed actions, opportunity, policy, and strategy. These are mechanistic variables only when operationalized. Demographic or cultural categories are context, not direct proof of latent mechanisms. ## 9. Non-claims This ontology does not claim that culture determines behavior, interaction history explains entire persons, cognition is directly observed, one grammar captures all interaction, representation is the sole cause of behavior, formalization eliminates ambiguity, one ontology replaces adjacent disciplines, or Fundamental proves FCI. ## 10. Current maturity | Concept | Status | |---|---| | Interaction participant | Proposed | | Domain commitments, state, semantics | Proposed | | Projection and representation | Proposed | | Scoped invariance | Proposed theory | | Opportunity profile | Proposed coordination framework | | Interaction episode | Proposed canonical unit | | Behavior and trace | Proposed | | Measurement contract | Proposed | | Typed similarity framework | Proposed | | Strategy | Proposed latent construct | | Formal foundation | Under investigation | | Predictive theory | Open | | Fundamental as research substrate | Proposed application | | FCI disciplinary autonomy | Unproven | ## Conclusion The ontology is a relational architecture for preserving distinctions among target, state, representation, access, coupling, behavior, evidence, comparison, and strategy. Its value depends on reproducible operationalization and comparative explanatory gain, not vocabulary breadth. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/02_Glossary/Computational_Interaction_Science_Glossary_v0.4.md (465 lines, 19.0 KiB) ======================================================================== # Foundations of Computational Interaction Glossary **Version:** Draft 0.4 **Status:** Provisional System of Record **Governance:** Concept Lifecycle and Theory Governance This glossary is the canonical vocabulary for the current Foundations of Computational Interaction (FCI) research program. Terms are organized by explanatory role rather than as a fixed implementation stack. Definitions remain provisional until empirically validated. ## Maturity labels - **Observation** — recorded phenomenon without an explanatory commitment. - **Idea** — speculative interpretation. - **Candidate** — defined concept under literature review and critique. - **Proposed** — bounded, operationalizable, and integrated into the provisional framework. - **Validated** — supported across multiple studies. - **Canonical** — stable foundational terminology. ## Domain commitments **Status:** Proposed A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology. **Boundary:** Domain commitments specify what the model admits. They do not by themselves assign meaning, produce a representation, or determine interpretation. ## System state **Status:** Proposed The physical, computational, social, or modeled condition of a declared system at a particular time. **Boundary:** State is not synonymous with data, meaning, representation, or observation. A state becomes content-bearing only under a specified semantics. ## Semantic assignment **Status:** Proposed A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain. **Boundary:** Formal semantic assignment is distinct from a person’s interpretation or understanding. ## Semantic state **Status:** Proposed The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state. **Boundary:** No observer-independent semantic state is assumed without an explicit theory and scope. ## Information **Status:** Proposed A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use. **Boundary:** Information is not a synonym for stored variables, data, meaning, semantic state, or interpretation. Every claim that information is preserved must name the information theory, source, code, task, or relevance criterion. ## Representation **Status:** Proposed A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice. A representation may preserve, transform, omit, or introduce structure. **Boundary:** A representation is not identical with its target. Equal reference does not imply semantic, inferential, behavioral, or interactional equivalence. ## Projection **Status:** Proposed analytical role A declared transformation from a target description, system state, or semantic assignment into an accessible representational form. A projection contract specifies: - target and authority; - mapping or construction rule; - interpretation assumptions; - preserved properties; - transformed properties; - omitted properties; - introduced properties; - available operations; - observer assumptions; - intended use; - context and scope; - uncertainty, tolerance, and failure conditions. **Boundary:** Projection coordinates established concepts such as views, abstractions, encodings, lenses, simulations, model morphisms, and renderings. It is not a new metaphysical substance. ## Scoped invariance **Status:** Proposed theory A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance. Invariance must be typed. Relevant types include: - ontological; - semantic; - informational; - structural; - topological; - computational; - inferential; - task; - behavioral; - interactional. **Boundary:** No one invariance type implies another. ## Interpretation **Status:** Proposed The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose. **Boundary:** Interpretation is a process or event. Semantics specifies or stabilizes admissible relations; interpretation applies or revises them. ## Interaction participant **Status:** Proposed Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction. A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning. **Boundary:** Interaction participant is the top-level role. More specific terms such as human participant, computational participant, institution, observer, mediator, autonomous agent, and AI agent should be used when their additional commitments matter. ## Agent **Status:** Proposed subtype An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization. **Boundary:** Agent is not the universal term for every participant. An AI model is not automatically an agent; it becomes part of an agentic system when observations, action-selection, and consequential operations are supplied. ## Environment **Status:** Proposed The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur. **Boundary:** The environment is not identical with what an agent can observe through a representation. ## Affordance **Status:** Established external construct An action-relevant relation between an agent’s effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist. **Boundary:** Affordance is not synonymous with permission, signaling, belief, execution success, or reversibility. ## Opportunity **Status:** Proposed coordination framework A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions. Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty. ## Opportunity profile **Status:** Proposed For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations: - domain-valid; - effectively capable; - permitted; - enabled; - reachable outcomes; - exposed; - signaled; - believed available; - expected consequences; - selected; - executed; - successful; - reversible or recoverable; - uncertainty and provenance. Selected, executed, and successful are trace predicates rather than availability sets. ## Capability **Status:** Proposed The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions. **Boundary:** Capability is distinct from permission. Security capability tokens must be named explicitly when that narrower meaning is intended. ## Permission **Status:** Proposed Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation. **Boundary:** A prohibited action may remain technically possible. ## Enablement **Status:** Proposed The condition in which an action’s current-state preconditions are satisfied. **Boundary:** Enablement is local to the current state and differs from multi-step reachability. ## Reachability **Status:** Proposed The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon. ## Exposure **Status:** Proposed Provision by the current projection of an executable access path to an operation. **Boundary:** An exposed operation may be hidden, poorly signaled, unknown, or inaccessible to a particular observer. ## Signaling **Status:** Proposed Perceivable information indicating an operation, condition, consequence, state, or recovery path. **Boundary:** A signal may be true, incomplete, ambiguous, or false. ## Discoverability **Status:** Proposed The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions. **Boundary:** Discoverability is not a static visual property. ## Believed action **Status:** Proposed latent variable An action represented by an agent as available, with an associated confidence and expected consequence. **Boundary:** Belief cannot be read directly from non-selection or task completion. It requires elicitation or a validated inferential model. ## Action **Status:** Proposed A declared intervention, command, operation, or behavior capable of participating in a state transition. **Boundary:** A low-level input such as a click or touch is not necessarily the semantic action under study. ## State transition **Status:** Proposed A change from one declared system state to another under a transition relation, process, or event. ## Observation **Status:** Proposed A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process. **Boundary:** Observation is not interpretation, inference, or evidence by itself. ## Situated behavior **Status:** Proposed A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model. **Boundary:** Representation does not determine behavior directly. ## Behavioral evidence **Status:** Candidate A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim. **Boundary:** A trace is evidence of what occurred. It is not direct evidence of intention, understanding, culture, personality, or protected identity. ## Behavioral equivalence **Status:** Candidate Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance. **Boundary:** Behavioral equivalence does not imply semantic, interpretive, strategy, learning, transfer, or interactional equivalence. ## Interactional equivalence **Status:** Candidate Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions. ## Interaction **Status:** Proposed scientific target A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence. **Boundary:** Interaction is not reducible to action, behavior, communication, computation, observation, state transition, feedback, or causation alone. Ordinary-language usage may be broader than the strict research definition. ## Interaction episode **Status:** Proposed canonical unit A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale. Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated. **Boundary:** A single isolated one-way causal effect is not an interaction episode under the strict definition unless it enters a recurrent or reciprocally constraining structure. ## Coupling **Status:** Proposed A relation or pathway through which a participant or shared medium can alter another participant's transition structure, reachable states, probabilities, timing, or constraints. ## Perturbation **Status:** Proposed A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes. ## Uptake **Status:** Proposed Incorporation of a perturbation into a participant's state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious. ## Recurrence **Status:** Proposed Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration. ## Interaction contract **Status:** Proposed reusable artifact A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions. ## Interaction morphology **Status:** Candidate The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality. **Boundary:** Morphology is not independent of all semantics or interpretation. A study must declare which content and operations are controlled. ## Interaction grammar **Status:** Candidate A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation. ## Interaction history **Status:** Candidate The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent’s later beliefs, policies, and interpretation. **Boundary:** Interaction history biases later behavior but does not fully explain or determine an individual. ## Trace **Status:** Proposed A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules. **Boundary:** A trace is not identical with behavior, action, policy, strategy, intention, or mechanism. ## Measurement contract **Status:** Proposed reusable artifact A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation. **Boundary:** A metric is not a construct. Numerical output does not justify a latent interpretation without a validated measurement relation. ## Interaction similarity **Status:** Proposed typed comparison framework A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain. **Boundary:** There is no context-free universal similarity score. ## Token identity **Status:** Proposed Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria. ## Type identity **Status:** Proposed Membership in the same abstraction-defined interaction class under explicit classification rules. ## Equivalence **Status:** Proposed Exact preservation under a declared comparison contract and observable set. Equivalence is always typed. ## Similarity **Status:** Proposed Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty. ## Incomparability **Status:** Proposed Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions. ## Similarity contract **Status:** Proposed reusable artifact A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile. ## Strategy **Status:** Proposed latent explanatory construct An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states. **Boundary:** A strategy is not a single action, raw trace, repeated sequence, explicit plan, policy alone, skill, habit, or intention. It must be supported through rival discrimination, diagnostic contingencies, uncertainty, and evidence appropriate to the claim. ## Strategy contract **Status:** Proposed reusable artifact A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain. ## Policy **Status:** Proposed A conditional relation from represented states, observations, or beliefs to action distributions. **Boundary:** A policy may be one component of a strategy. Strategy may additionally include information acquisition, commitment, resource allocation, switching, recovery, and stopping rules. ## Fundamental **Status:** Proposed research substrate A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected. **Boundary:** Fundamental is not the scientific theory, a philosophical ontology, proof of FCI, or a guarantee of shared human meaning. ## Foundations of Computational Interaction **Status:** Proposed research program; disciplinary autonomy unproven A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence. FCI must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/03_Encyclopedia/Computational_Interaction_Science_Encyclopedia_Article_Draft_v0.3.md (327 lines, 30.9 KiB) ======================================================================== # Foundations of Computational Interaction > **Editorial status:** Canonical encyclopedia-style draft, version 0.3. This is not yet suitable for Wikipedia mainspace because *Foundations of Computational Interaction* does not presently have significant independent secondary coverage. The origin statement concerning Zachary Shallbetter and Fundamental should remain project-documented provenance until independently sourced. **Foundations of Computational Interaction** (**FCI**) is a proposed interdisciplinary research program concerned with the systematic study of computational interaction, including its representation, coupling, behavioral organization, measurement, and comparison. It examines how human, computational, collective, institutional, and hybrid participants become mutually consequential through computationally mediated representations, interpretations, opportunities, actions, state transitions, and feedback. FCI treats **interaction** as its principal explanatory target rather than reducing it to interface use, individual behavior, communication, or machine execution. Its research program seeks to determine which properties of an interaction remain stable, which change, and why, when the system, representation, modality, participant, context, authority, history, or implementation changes. The proposed field draws on [[human–computer interaction]], [[computer science]], [[cognitive science]], [[artificial intelligence]], [[information science]], [[ecological psychology]], [[cybernetics]], [[control theory]], [[formal methods]], [[distributed cognition]], and the [[philosophy of science]]. It remains a developing theoretical program rather than a recognized independent academic discipline. ## Terminology The full name is **Foundations of Computational Interaction**. The shortened form **FCI** is used as a practical name for the research program and as an adjective in phrases such as *FCI model* and *FCI experiment*. The adjective *computational* identifies both the phenomenon and the method. FCI includes interaction in which computation participates directly, as in software, AI, robotics, protocols, and computational infrastructure. It also uses computational methods such as simulation, formal modeling, trace analysis, replay, and reproducible comparison. FCI uses **interaction participant** as its broadest term for an entity occupying a consequential role in an interaction. This avoids using *agent* as a universal category. In contemporary artificial intelligence, *agent* commonly denotes a computational system that selects and performs actions with some autonomy. FCI therefore reserves *agent* for participant types whose action-selection properties are relevant and explicitly stated. An interaction participant may be a person, software service, AI system, robot, team, institution, organization, sensor, policy engine, or hybrid arrangement. Participation does not imply consciousness, intelligence, autonomy, or learning. A participant may instead observe, mediate, authorize, constrain, translate, store, represent, or transform state. ## Origins and development The term *Foundations of Computational Interaction* was introduced in project documentation by **Zachary Shallbetter** during the development of **Fundamental**, a representation-independent computational substrate, in 2025–2026. The initial engineering problem concerned how one declared computational world could be realized across games, user interfaces, data systems, native applications, simulations, and other hosts without being defined by any one representation. Questions raised by that architecture moved beyond software design. If the same target system could be expressed through different representations, researchers could ask what each representation preserved, transformed, omitted, or introduced. If the underlying operations remained stable while visibility, signaling, or interaction changed, those differences could be treated as experimental variables rather than aesthetic judgments. Fundamental consequently became one possible research substrate for the emerging theory rather than the theory itself. This provenance is documented within the FCI project. It should not be presented as independently established public history unless reliable secondary sources attribute the term and its origin. Early FCI research examined how sciences stabilize explanatory targets, how representations differ from their targets, and how ontology, semantics, information, interpretation, and behavior should be separated. Later work developed a typed account of action opportunity connecting system-relative possibility to what participants can perceive, believe, execute, and recover from. These studies weakened several strong initial claims. Representation was not found to determine behavior; semantic equivalence did not imply equivalent interpretation or action; opportunity did not emerge as a new primitive; and interaction did not yet justify an autonomous discipline. The surviving contribution was a relational architecture coordinating established concepts while preserving their distinct sources of truth and evidence. ## Scientific object FCI studies computational interaction as an **explanatory target**. An explanatory target is the event, pattern, capacity, regularity, outcome, or contrast for which an account is sought. Treating interaction as a target does not imply that interaction belongs exclusively to one discipline or that it is a natural kind with a single essence. In broad usage, computational interaction is a temporally situated coupling in which computationally mediated participants, systems, representations, actions, and feedback become mutually consequential. For research requiring a discriminating episode boundary, FCI uses a stricter definition: > **An interaction episode is a bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale.** Reciprocal closure may be direct, asymmetric, delayed, probabilistic, or mediated through a shared environment. A single isolated one-way causal effect is therefore causation but not necessarily an interaction episode under the strict definition. An interaction may be analyzed at several levels: a synchronized event, recurrent exchange, task episode, long-term practice, team, institution, or longitudinal relationship. No universal smallest unit has been established; the boundary and timescale are part of the research claim. Interaction is distinguished from neighboring concepts. An **action** is an intervention, command, or behavior that may participate in a state transition. A **state transition** is a change in a declared system state. **Communication** concerns messages and signals. **Computation** concerns formally or physically realized transformations. These may occur within interaction, but none alone defines the complete explanatory target. ## Theoretical framework FCI uses a relational rather than strictly layered model. It distinguishes roles that are frequently combined in software systems or research accounts while allowing them to constrain and revise one another. ### Domain commitments, state, and semantics **Domain commitments** specify the entities, relations, identities, constraints, modalities, and operations admitted by a model or inquiry. They may be expressed through a formal ontology, conceptual model, schema, type system, contract, or protocol. **System state** is the physical, computational, social, or modeled condition of the declared system at a particular time. State may include values, entities, relationships, permissions, resources, histories, and process conditions. Stored variables are therefore components of state or data, not meaning by themselves. **Semantic assignment** is the rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations. In logic, an interpretation supplies truth conditions. In programming-language theory, denotational, operational, and axiomatic semantics provide different accounts of program behavior. These formal assignments can be specified independently of whether a human participant understands them. A **semantic state** is the set of content-bearing assignments and relations currently licensed by a specified semantics. FCI does not assume that every semantic state is observer-independent. ### Representation and projection A **representation** is a materially or formally realized vehicle that provides selective access to a declared target through a mapping and an interpretive practice. Representations include diagrams, source code, maps, tables, interfaces, simulations, speech, tactile displays, documents, and APIs. Representation is selective and constructive. It may preserve some entities, relations, quantities, or operations while transforming or omitting others. It may also introduce structure not present in the source description, such as spatial grouping, row order, visual salience, coordinate systems, defaults, interaction sequences, latency, or ambiguity. A **projection** is a declared transformation from a target description, system state, or semantic assignment into an accessible representational form. It coordinates established ideas such as database views, abstraction functions, bidirectional lenses, cartographic projections, compiler transformations, scientific models, and interface renderings. A projection contract specifies the target, mapping, interpretation rules, preserved properties, transformed properties, omissions, introduced properties, available operations, observer assumptions, intended uses, uncertainties, tolerances, and failure conditions. ### Scoped invariance FCI rejects unqualified claims that two representations have “the same meaning” or contain “the same information.” Invariance is typed and scoped. Let \(T\) be a declared target domain, \(R_1\) and \(R_2\) representation domains, and \(p_1:T\rightarrow R_1\) and \(p_2:T\rightarrow R_2\) projection functions. Let \(J_1\) and \(J_2\) be independently specified interpretation or comparison functions, \(Q\) the property family claimed invariant, and \(\varepsilon\) the permitted tolerance. Scoped invariance holds when \[ J_1(p_1(t)) \equiv_Q J_2(p_2(t)) \pm \varepsilon \] for the declared targets, observers, tasks, and contexts. The property family \(Q\) may concern identity, truth conditions, topology, computational behavior, inferential consequences, task outcomes, behavior, or interactional structure. Preservation of one type does not imply another. Two interfaces may be computationally equivalent while producing different inference, recovery, effort, or action distributions. ### Interpretation **Interpretation** is the application, recovery, construction, negotiation, or revision of semantic relations by an interpreting participant or practice under a context, competence, history, and purpose. Interpretation is distinct from formal semantics. A program may possess stipulated operational semantics while users misunderstand its interface. Multiple communities can interpret the same representation differently, and interpretation can change through action and feedback. This distinction constrains behavioral inference: equivalent actions or outcomes do not prove equivalent interpretations. ### Opportunity and action availability FCI uses **opportunity** as a typed coordination framework rather than a new primitive. The model integrates concepts from ecological affordance theory, planning, control, access control, decision theory, reinforcement learning, formal methods, and HCI. For an action \(a\), participant \(x\), state \(s\), projection \(p\), and time \(t\), an opportunity profile may record whether the action is domain-valid, within the participant-system capability, permitted, currently enabled, capable of reaching a target outcome, exposed by the projection, signaled, believed available, expected to have particular consequences, reversible, selected, executed, and successful. A compact representation is: \[ \Omega_t(a,x)= \langle D,C,M,N,L,X,G,B,Q,V,U \rangle \] where \(D\) denotes domain validity, \(C\) effective capability, \(M\) permission, \(N\) current enablement, \(L\) reachable outcomes, \(X\) exposure, \(G\) signaling, \(B\) believed availability, \(Q\) expected consequences, \(V\) reversibility or recoverability, and \(U\) uncertainty and provenance. The tuple coordinates different relations; it does not imply that they share one bearer or measurement method. Permission is determined by authority or policy. Enablement is determined by current-state preconditions. Exposure is a property of a projection and access path. Signaling involves perceivable cues. Belief is participant-relative and latent. Selection, execution, and success are observed events or trace predicates. ### Policy, behavior, and feedback A **policy** is a decision or action-selection process conditioned by interpreted state, goals, capability, authority, expected consequences, environment, history, costs, risk, and uncertainty. Situated behavior is not modeled as a direct function of representation. A schematic relation is \[ B_t \sim \pi(J_t,\Omega_t,G_t,E_t,K_t,H_t) \] where \(J_t\) is interpreted state, \(\Omega_t\) the opportunity profile, \(G_t\) goals, \(E_t\) the surrounding environment, \(K_t\) relevant capabilities or knowledge, and \(H_t\) interaction history. The resulting action changes the system through a transition relation: \[ X_{t+1}=T(X_t,B_t) \] The transition may also alter later permissions, representations, interpretations, beliefs, and recovery paths. FCI therefore treats interaction as recursive. ## Computational interaction model A computational interaction episode may be represented analytically as \[ \mathcal{C}_t = \langle O,X,S,P,R,I,\Omega,\pi,B,E_v \rangle_t \] where \(O\) denotes domain commitments, \(X\) system state, \(S\) semantic assignment, \(P\) projection, \(R\) representational realization, \(I\) interpretation, \(\Omega\) opportunity profile, \(\pi\) policy, \(B\) situated behavior, and \(E_v\) the evidence record. The tuple is an analytical decomposition, not a claim that every interaction literally implements ten software modules or cognitive variables. Its purpose is to prevent claims from moving between levels without justification. An interaction evolves as \[ \mathcal{C}_t \rightarrow \mathcal{C}_{t+1} \] through system transitions, changed representations, revised beliefs, learning, institutional action, and accumulated evidence. ## Behavior, measurement, similarity, and strategy FCI distinguishes behavior from raw records. **Behavior** is treated as a bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation model. A log record may support detection of an event; an event may support an attributed trace; neither alone establishes an action, policy, strategy, intention, or understanding. Measurement supplies the bridge from observation to scientific claim. A **Measurement Contract** declares the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, and permitted interpretation. FCI therefore treats a metric and a construct as different objects. Completion time, for example, is a measured duration; it is not by itself a measure of comprehension, confidence, fluency, or quality. Interaction comparison is typed rather than universal. Token identity concerns the same historical episode. Type identity concerns membership in the same abstraction-defined class. Equivalence concerns exact preservation under declared observables and admissible transformations. Similarity concerns graded proximity under specified dimensions and metrics. Incomparability occurs when no defensible common comparison space can be established. A similarity contract can be summarized as \[ K = \langle T,F,M,O,A,D,W,\varepsilon,U,V \rangle \] where the terms declare target type, comparison frame, correspondence mapping, observables, admissible transformations, typed distances, weighting, tolerances, uncertainty, and validity domain. The preferred result is a typed profile across semantic, structural, protocol, opportunity, trace, behavioral, policy, strategy, outcome, causal, and measurement-relative dimensions rather than one composite score. An **interaction strategy** is an inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of states. Strategy is supported by traces but is not identical with them. It may contain a policy or plan, but may also require information-seeking, commitment, recovery, switching, stopping, and distributed coordination. A strategy model may be expressed analytically as \[ \Sigma = \langle D,X,O,Z,C,A,\pi,q,k,r,w,\tau,\rho,U \rangle \] where the components describe the domain, state, observation model, state abstraction, criteria, action repertoire, conditional selection, information acquisition, commitments, recovery, switching, stopping, resources, and uncertainty. The tuple is an analytical contract, not a claim about the literal structure of human cognition. Strong strategy claims require rival models, diagnostic contingencies, repeated evidence, and preferably intervention or out-of-sample discrimination. ## Interaction participants An **interaction participant** is any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role in an interaction. One entity may occupy several roles simultaneously. A conversational AI may represent system state, interpret a request under an operational model, mediate access to external tools, select an action, and generate signals that alter a human participant's beliefs. A policy engine may authorize or prevent transitions without interpreting in a human sense. An **autonomous agent** is an acting participant that selects actions through an internally maintained policy under observed or inferred state. An **AI agent** is a computational participant whose action selection substantially depends on an AI model and whose host system supplies observations and consequential operations. A model that only produces text or classifications is not automatically an agent. The term **observer** identifies a role occupied by a participant when it receives, measures, records, or constructs distinctions concerning a target. The observer need not be external to the system. ## Evidence and methodology FCI distinguishes direct observations from derived features, latent interpretations, and research conclusions. \[ \text{observation} \rightarrow \text{derived feature} \rightarrow \text{model-dependent interpretation} \rightarrow \text{bounded claim} \] Each step requires provenance, uncertainty, alternative explanations, and falsifying conditions. A pause in an action trace is an observed duration, not direct evidence of hesitation. Failure to select an action does not prove that the participant was unaware of it. Successful completion does not establish understanding. Cultural, demographic, or protected identities cannot be inferred from interaction behavior. Methods proposed for FCI include controlled experiments, formal verification, simulation, trace analysis, replay, observational studies, qualitative inquiry, mixed methods, and longitudinal research. The program now coordinates Projection, Opportunity, Interaction, Behavioral Evidence, Measurement, Similarity, and Strategy Contracts so that each inferential transition remains inspectable. A projection comparison should declare the target model, operation semantics, authority rules, starting states, participant population, tasks, equivalence type, measurement procedures, tolerances, and implementation differences. Formal claims may be tested through query equivalence, reconstruction, refinement, bisimulation, model checking, or verified transition correspondence. Empirical claims may involve discovery, latency, action awareness, belief calibration, sequence choice, error, recovery, learning, transfer, accessibility, effort, and coordination. ## Applications In **human–AI interaction**, FCI can compare what an AI system can execute with what its language implies, what policy permits, and what users believe. This distinguishes fluent explanation from actual authority and capability. In **accessibility**, one transit system may be exposed through a visual map, structured speech, tactile output, and a programmatic interface. Route semantics may remain stable while search cost, spatial overview, memory demand, privacy, recovery, and independent verification differ. In **scientific visualization**, equations, diagrams, simulations, tables, and narratives may concern the same target model while supporting different inferences. In **software development**, a version-control repository may be operated through a graphical interface, command line, API, or conversational assistant. Core transitions may be computationally equivalent even though discoverability, composition, auditability, and failure prevention differ. In **robotics**, a robot, remote operator, supervisor, sensor system, and policy service may interact through different projections of one physical environment. In **healthcare**, clinicians, patients, insurers, scheduling systems, and regulators may receive role-specific projections of a shared workflow, each with different information, authority, language, and consequences. In **games and simulation**, one declared world may be projected through particles, maps, text, spatial interfaces, or automated participants, providing controlled environments for studying representation, opportunity, coordination, learning, and behavior. ## Relationship to adjacent fields FCI overlaps substantially with existing disciplines and does not claim to replace them. [[Human–computer interaction]] studies the design, use, and consequences of interactive computational systems. the model proposes a more general explanatory architecture intended to apply across human, computational, institutional, and hybrid participants. Whether this difference warrants a separate field remains unresolved. [[Cybernetics]] studies communication, control, and feedback in animals, machines, and organizations. FCI inherits this concern with coupled systems while giving explicit attention to representation, interpretation, typed opportunity, and cross-projection equivalence. [[Cognitive science]] studies perception, reasoning, learning, language, and action. FCI may use cognitive theories but does not require every interaction explanation to posit internal cognition. [[Artificial intelligence]] and [[multi-agent system]] research study intelligent action, coordination, planning, learning, and autonomous systems. FCI includes non-autonomous participants and focuses on how representations, authority, interpretation, and action availability structure interaction. [[Information science]] studies the creation, representation, organization, retrieval, flow, and use of information. FCI treats information as a typed component of a broader interaction account. [[Formal methods]] and programming-language theory supply precise accounts of state, transition, semantics, refinement, equivalence, and verification. FCI attempts to connect these formal relations with human interpretation, accessibility, institutional authority, and empirical behavior. [[Ecological psychology]] supplies the relational concept of affordance, while activity theory, situated action, and distributed cognition emphasize tools, practices, communities, and material organization. FCI integrates these with computational transition systems, access control, and projection analysis. [[Computational social science]] uses computation to study social systems and behavior. FCI instead takes computational interaction itself as the target and can include non-social cases such as compiler interfaces, machine protocols, or robot-control systems. ## Fundamental **Fundamental** is a computational substrate associated with the origins of FCI. It separates declared model commitments, system state, operational behavior, projection, and host realization. Its concepts include bodies, relationships, patterns, contracts, projections, queries, snapshots, and replay. Within FCI, Fundamental is treated as one possible research instrument. It can help researchers hold declared model state constant while generating different projections, verify formal preservation properties, expose operations, and connect behavioral traces to the alternatives and state present at the time of action. Fundamental does not validate FCI, guarantee shared interpretation, or replace participant research, consent, statistical analysis, qualitative methods, or causal identification. ## Criticism and open questions The principal criticism of FCI is that it may represent a synthesis of existing theories rather than a distinct explanatory program. Its major concepts already exist in philosophy, computer science, HCI, psychology, control theory, and formal methods. The framework must therefore demonstrate that its relational integration produces measurable explanatory, predictive, or intervention gains rather than merely reorganizing vocabulary. A related concern is overformalization. Typed models can create false precision when interpretation, culture, social practice, or institutional power cannot be adequately expressed as variables. FCI treats its formal models as analytical commitments and requires qualitative and contextual methods where appropriate, but the adequacy of that response remains empirical. Measurement has been specified as a contract-based framework, but empirical validation remains unresolved. Believed action availability, interpretation, expected consequence, perceived reversibility, strategy, and transfer are not directly observable. Their reliability and measurement invariance across tasks, languages, cultures, modalities, and populations have not been established. The status of interaction as a distinct explanatory level also remains unsettled. Existing theories may explain interaction phenomena sufficiently when integrated, leaving FCI as a useful cross-disciplinary framework rather than an autonomous science. Other open questions include formal model selection, strategy identifiability, interaction transfer, predictive limits, interaction grammar and morphology, causal equivalence, longitudinal history, and generalization beyond structured computational tasks. ## Current status Foundations of Computational Interaction is a proposed research program. Its current contributions are theoretical synthesis, a strict interaction definition, behavior and evidence hierarchies, measurement requirements, typed similarity and strategy frameworks, reusable contracts, operational hypotheses, and a research agenda. It has not established a recognized discipline, a validated universal ontology, or a demonstrated body of predictive laws. Its strongest current claim is methodological: > Computational interaction should be studied by declaring the target system and episode boundary; separating state, representation, interpretation, opportunity, coupling, behavior, measurement, comparison, and strategy; preserving evidence provenance; and testing typed invariance, equivalence, similarity, and causal claims rather than assuming them. ## See also [[Human–computer interaction]] · [[Interaction design]] · [[Cognitive science]] · [[Cybernetics]] · [[Systems theory]] · [[Distributed cognition]] · [[Situated cognition]] · [[Ecological psychology]] · [[Affordance]] · [[Formal methods]] · [[Programming language semantics]] · [[Knowledge representation and reasoning]] · [[Information visualization]] · [[Human–robot interaction]] · [[Human–AI interaction]] · [[Multi-agent system]] · [[Computational social science]] ## Selected references Abbott, Andrew. *Chaos of Disciplines*. University of Chicago Press, 2001. Baier, Christel, and Joost-Pieter Katoen. *Principles of Model Checking*. MIT Press, 2008. Card, Stuart K.; Moran, Thomas P.; and Newell, Allen. *The Psychology of Human–Computer Interaction*. Lawrence Erlbaum Associates, 1983. Cleveland, William S., and Robert McGill. “Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods.” *Journal of the American Statistical Association* 79 (1984): 531–554. Codd, Edgar F. “A Relational Model of Data for Large Shared Data Banks.” *Communications of the ACM* 13 (1970): 377–387. Cousot, Patrick, and Radhia Cousot. “Abstract Interpretation: A Unified Lattice Model for Static Analysis of Programs by Construction or Approximation of Fixpoints.” *Proceedings of POPL* (1977): 238–252. Daston, Lorraine, and Peter Galison. *Objectivity*. Zone Books, 2007. Gaver, William W. “Technology Affordances.” *Proceedings of CHI 1991* (1991): 79–84. Gibson, James J. *The Ecological Approach to Visual Perception*. Houghton Mifflin, 1979. Giere, Ronald N. *Scientific Perspectivism*. University of Chicago Press, 2006. Gruber, Thomas R. “A Translation Approach to Portable Ontology Specifications.” *Knowledge Acquisition* 5 (1993): 199–220. Guarino, Nicola. “Formal Ontology and Information Systems.” *Proceedings of FOIS '98* (1998): 3–15. Hacking, Ian. *Representing and Intervening*. Cambridge University Press, 1983. Hutchins, Edwin. *Cognition in the Wild*. MIT Press, 1995. Kuhn, Thomas S. *The Structure of Scientific Revolutions*. 2nd ed. University of Chicago Press, 1970. Larkin, Jill H., and Herbert A. Simon. “Why a Diagram Is (Sometimes) Worth Ten Thousand Words.” *Cognitive Science* 11 (1987): 65–100. Machamer, Peter; Darden, Lindley; and Craver, Carl F. “Thinking About Mechanisms.” *Philosophy of Science* 67 (2000): 1–25. Norman, Donald A. *The Design of Everyday Things*. Revised ed. Basic Books, 2013. Peirce, Charles Sanders. *Collected Papers of Charles Sanders Peirce*. Harvard University Press, 1931–1958. Shannon, Claude E. “A Mathematical Theory of Communication.” *Bell System Technical Journal* 27 (1948): 379–423 and 623–656. Simon, Herbert A. *The Sciences of the Artificial*. 3rd ed. MIT Press, 1996. Suchman, Lucy A. *Plans and Situated Actions*. Cambridge University Press, 1987. Tarski, Alfred. “The Semantic Conception of Truth and the Foundations of Semantics.” *Philosophy and Phenomenological Research* 4 (1944): 341–376. Wiener, Norbert. *Cybernetics: Or Control and Communication in the Animal and the Machine*. MIT Press, 1948. Woodward, James. *Making Things Happen: A Theory of Causal Explanation*. Oxford University Press, 2003. Zhang, Jiajie, and Donald A. Norman. “Representations in Distributed Cognitive Tasks.” *Cognitive Science* 18 (1994): 87–122. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/04_Framework/Fundamental_and_Computational_Interaction_Science_v0.4.md (261 lines, 10.4 KiB) ======================================================================== # Fundamental and Foundations of Computational Interaction ## Declared Worlds, Governed Projections, and Empirical Interaction **Version:** Draft 0.4 **Status:** Concept Paper ## Abstract Fundamental and Foundations of Computational Interaction are complementary but distinct. Foundations of Computational Interaction (FCI) is a proposed research program for studying interaction as an explanatory target. It separates domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, interaction episodes, behavior, measurement, similarity, strategy, and evidence so that their relationships can be examined rather than assumed. Fundamental is a representation-independent computational substrate. It can declare model commitments, evolve state, apply operational semantics, generate governed projections, expose typed operations, and preserve inspectable snapshots, diffs, and replay. It is not a philosophical ontology, a theory of human meaning, or evidence that FCI is correct. The connection is methodological. FCI requires controlled distinctions and contract-based provenance. Fundamental can make a subset of those distinctions executable, including projection, opportunity, interaction-state, replay, and comparison inputs. ## 1. The shared problem Most software systems tightly bind: - domain model; - application state; - rendering; - available controls; - user-facing interpretation; - telemetry. When these move together, a representation change often changes the modeled system, executable action set, or instrumentation. Researchers cannot determine whether a behavioral difference came from projection, implementation, authority, latency, semantics, or task structure. FCI requires those sources of variation to be declared separately. Fundamental supplies an architecture in which they can be separated enough to inspect and manipulate. ## 2. Fundamental’s supported claim The earlier claim that Fundamental preserves a universal semantic reality was too strong. The defensible claim is: > Fundamental can preserve declared domain commitments, identities, relations, constraints, state transitions, and selected operational semantics across governed projections, within explicit scope and equivalence conditions. Fundamental does not guarantee: - identical human interpretation; - equal understanding; - behavioral equivalence; - cultural neutrality; - accessibility equivalence; - invariant information under every theory; - invariant implementation cost; - observer-independent meaning. ## 3. Computational roles ### Domain commitments Bodies, identities, relationships, constraints, rules, and contracts instantiate a declared model of what the runtime admits. These are computational commitments, not metaphysical proof about what exists. ### System state The runtime contains the current modeled condition: registered bodies, relationships, metrics, active patterns, transitions, history, and other declared state. ### Operational semantics Forces, relationships, contracts, update rules, and host operations assign transition behavior to declared state. The semantics is operational and inspectable. It does not by itself establish human meaning. ### Projection A Fundamental projection maps selected state or semantic relations into a host-accessible form. A projection may target: - DOM and CSS; - Canvas or SVG; - native UI; - sound or haptics; - spatial systems; - agent-readable JSON; - diagnostics; - headless queries; - physical installations. Projection is replaceable, but not neutral. ### Representation The host realizes a representation with introduced ordering, geometry, grouping, salience, modality, latency, interaction operations, and accessibility conditions. ### Opportunity A projection may alter: - which runtime operations are exposed; - which actions are signaled; - which actions an observer believes are available; - sequence cost; - feedback; - auditability; - recovery visibility; - actual feasibility when the projection gates operations. Fundamental can declare and inspect the system-relative portion of an opportunity profile. Agent belief and interpretation require empirical measurement. ## 4. Projection as a governed contract A Fundamental projection should declare: - source model and version; - target host or modality; - mapping rule; - preserved identities and relations; - transformed properties; - omitted properties; - introduced properties; - exposed operations; - signifiers and feedback; - update correspondence; - observer and accessibility assumptions; - intended use; - uncertainty and latency; - failure conditions. A projection is valid for a claim only when the contract is appropriate to that claim. “Shows the same world” is not sufficient. ## 5. Scoped invariance Fundamental can support tests of typed invariance: - stable identity across hosts; - preservation of declared relationships; - query or inferential equivalence; - trace or transition equivalence; - compatible state snapshots; - operation correspondence; - accessibility of declared content; - behavioral or task equivalence through external studies. The first group can often be verified computationally. The latter claims require empirical evidence. ## 6. Why portability follows Fundamental has been implemented across languages and environments because its central commitments are not tied to a particular rendering library. Portability comes from the separability of: ```text declared model operational state projection contract host realization ``` The code is portable because the conceptual roles are portable. This does not imply that every implementation is behaviorally or operationally equivalent. Each port must declare preserved semantics, numeric tolerances, timing differences, host limitations, and failure modes. ## 7. Fundamental as a research instrument Fundamental can support FCI by enabling researchers to: 1. declare one target model; 2. preserve stable identities and transitions; 3. produce multiple projection contracts; 4. verify formal preservation independently; 5. enumerate exposed operations and reachable states; 6. capture snapshots and replay; 7. compare projection-specific opportunity profiles; 8. connect behavioral telemetry to the state and alternatives present at the moment of action. Its scientific value lies in controlling confounds, not in replacing research methodology. ## 8. Interaction, measurement, similarity, and strategy support Fundamental can support an **Interaction Contract** by exposing participant roles represented in the model, boundaries, state, coupling channels, preconditions, semantic events, transitions, invariants, failures, and completion conditions. It cannot by itself decide every socially or empirically appropriate episode boundary. Its snapshots, event traces, and deterministic replay can support the lower levels of a **Behavioral Evidence Contract**, but raw engine events remain records. Semantic action attribution, participant interpretation, and behavioral claims require declared observation and coding rules. Fundamental can support a **Measurement Contract** by preserving source variables, formulas, versions, missingness, timing, and provenance. It cannot turn a metric into a validated human construct. It can also support a **Similarity Contract** by providing stable identifiers, correspondence mappings, state and transition models, projection contracts, admissible transformation checks, typed distances, and replayable cases. The default result should remain a typed profile rather than a scalar ranking. Strategy is mostly outside the runtime. Fundamental may represent or execute an artificial policy and can supply evidence about information requests, switching, recovery, and action selection. Human or collective strategy remains a latent attribution requiring rival models, diagnostic interventions, uncertainty, and external analysis. ## 9. What remains outside Fundamental Fundamental should not own: - participant identity and consent; - study assignment and randomization; - cultural or demographic inference; - psychometric constructs; - belief measurement; - qualitative interpretation; - statistical analysis; - causal identification; - longitudinal participant records; - publication claims. Those belong to a separate research layer. ## 10. Relationship to FCI FCI supplies the explanatory questions: - Which properties remain invariant? - Which projection properties reorganize epistemic access? - Which actions are feasible, exposed, signaled, believed, and recoverable? - Which behavioral differences survive controls? - Which models outperform existing integrated accounts? Fundamental supplies a controlled computational substrate for some of those questions. Neither proves the other. ## 11. Current architectural statement A concise description is: > Fundamental is a representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected. A concise statement of the relationship is: > Foundations of Computational Interaction studies the relations among declared systems, projections, interpretation, opportunity, coupling, behavior, measurement, similarity, and strategy; Fundamental makes a bounded subset of those relations executable, replayable, and inspectable. ## 12. Falsification and limits The claimed relationship should be narrowed if: - projection and source model cannot be separated in practice; - ports fail to preserve declared operational semantics; - projection contracts add no diagnostic or experimental value; - opportunity structures cannot be enumerated reliably; - behavioral studies gain no explanatory value from Fundamental’s state and replay; - a simpler architecture controls the same variables with less complexity. ## Conclusion Fundamental is not merely a renderer, but neither is it a complete theory of meaning or interaction. Its distinctive contribution is architectural explicitness: ```text model commitments ≠ state ≠ operational semantics ≠ projection ≠ host representation ≠ interpretation ≠ behavior ``` That separation makes projection replaceable, preservation claims testable, and interaction experiments less confounded. FCI explains why those distinctions matter scientifically. Fundamental provides one way to instantiate them computationally. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/05_Specifications/Contracts/Computational_Interaction_Science_Contracts_v1.0.0-structure.1.md (292 lines, 12.6 KiB) ======================================================================== # Foundations of Computational Interaction Contracts Version: 1.0.0-structure.1 Status: Derivative consolidation; source papers remain authoritative until normative ratification. ## Scope This document consolidates contract artifacts already present in the research papers. It introduces no new theoretical fields. Each section records its source paper and extraction heading. Empty or terse sections indicate that the source artifact was represented primarily through tables or adjacent text and requires later normative review. ## Projection Contract Source: `02_Research_Papers/.../Representation_Invariance_and_Projection.docx` Extraction heading: `C. Projection Contract` ### C. Projection Contract | Field | Required declaration | | --- | --- | | Target domain | What is represented; authority and version; boundaries and granularity. | | Representation domain | Vehicle/form and admissible instances. | | Mapping | Construction, encoding, measurement, query, or transformation rule. | | Interpretation | Semantics, conventions, training, and decoding assumptions. | | Preserved properties | Relations, quantities, behaviors, consequences, or operations retained. | | Transformed properties | Changes of coordinate, scale, order, granularity, modality, or dynamics. | | Omitted properties | Distinctions unavailable or unrecoverable. | | Introduced properties | Categories, saliences, defaults, ambiguity, artifacts, or noise. | | Available operations | Read, query, compare, manipulate, update, undo, coordinate, export. | | Observer assumptions | Capabilities, knowledge, language, access needs, and role. | | Intended use | Questions, decisions, tasks, and prohibited uses. | | Uncertainty and error | Provenance, confidence, distortion, latency, and tolerance. | | Failure conditions | Known counterexamples, out-of-scope states, and invalid inferences. | ## Opportunity Contract Source: `02_Research_Papers/.../Opportunity_Affordance_and_Action_Availability.docx` Extraction heading: `C. Opportunity Contract` ### C. Opportunity Contract Projection contract Identity • Declared target system, task, agent class, state scope, and comparison time. • Projection identifier and modality. System-relative action structure • Domain-valid action vocabulary and transition semantics. • Effective capability requirements. • Permission and authority rules. • Current enablement predicates. • Reachable outcomes and path constraints. • Failure modes and irreversible effects. Projection-relative structure • Exposed operations and access paths. • Signifiers, labels, conventions, and feedback. • Hidden prerequisites and external documentation. • Ordering, composition, audit, and recovery support. Observer assumptions • Sensory and motor access. • Language, conventions, training, and prior exposure. • Available assistive technologies. • Goal and risk context. Epistemic variables • Believed action distribution. • Expected consequence distribution. • Confidence and uncertainty. • Perceived reversibility and cost. Validity • Intended use. • Metrics and tolerances. • Known omissions. • Conditions under which comparisons fail. ## Interaction Contract Source: `02_Research_Papers/.../Interaction_Toward_a_General_Theory_of_Interaction.docx` Extraction heading: `Interaction Contract` ### Interaction Contract | Element | Definition / specification | | --- | --- | | Identity | interaction type and token identifier; abstraction level | | Participants | entities, roles, capabilities, authority, and inclusion criteria | | Boundary | system/environment partition; timescale; start and closure rules | | State | relevant state variables and uncertainty | | Coupling | channels, shared media, topology, latency, and capacity | | Preconditions | eligibility, permissions, enablement, and initial assumptions | | Events | emission, transmission, uptake, response, recurrence, commitment, failure | | Transitions | deterministic, nondeterministic, or probabilistic state effects | | Protocol | admissible ordering, synchronization, obligations, and timeouts | | Invariants | properties required to remain preserved | | Evidence | direct observations, derived dependencies, inferred interpretations | | Failure and recovery | deadlock, rejection, timeout, compensation, cancellation, rollback | | Completion | stable termination, commitment, goal condition, timeout, or declared truncation | ## Behavioral Evidence Contract Source: `02_Research_Papers/.../Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx` Extraction heading: `15. Behavioral Evidence Contract` ### 15. Behavioral Evidence Contract | Field | Required declaration | | --- | --- | | Target system | Boundary, level, and ownership criteria. | | Environment | Relevant external entities, conditions, institutions, and other agents. | | Observation model | Sensors, logs, coding scheme, channels, sampling, and calibration. | | Temporal model | Clock, ordering, latency, synchronization, interval conventions. | | Event vocabulary | Types, detection rules, segmentation, and granularity. | | Attribution rule | Why an event is assigned to a system and with what confidence. | | Context | Task, projection, opportunity profile, permission, history, and incentives. | | Outcome criteria | Success, failure, cost, reward, safety, or completion definitions. | | Latent constructs | Measurement model, indicators, alternatives, and identification assumptions. | | Uncertainty | Missing data, detector error, attribution ambiguity, and confidence. | | Comparison scope | Populations, systems, settings, invariants, metrics, and tolerances. | | Failure conditions | Conditions under which the trace cannot support the intended claim. | ## Measurement Contract Source: `02_Research_Papers/.../Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx` Extraction heading: `10. Measurement Contracts` ### 10. Measurement Contracts Every reported interaction measure should be accompanied by a measurement contract containing: 1. Construct and intended interpretation. 2. Measurand and unit of analysis. 3. Scope conditions: population, task, system, projection, context, and time. 4. Observation model and instrument. 5. Event, state, and boundary definitions. 6. Operationalization and indicators. 7. Transformation, coding, or estimator. 8. Scale type and permissible operations. 9. Missingness, exclusions, and preprocessing. 10. Reliability evidence. 11. Validity evidence. 12. Uncertainty budget. 13. Comparison and invariance assumptions. 14. Failure conditions and prohibited interpretations. 15. Reproducibility artifacts. This contract is the minimum reusable unit of measurement specification. It makes the evidential chain inspectable and supports later interaction-similarity and comparative-interaction research. ## Similarity Contract Source: `02_Research_Papers/.../Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx` Extraction heading: `D. Similarity Contract` ### D. Similarity Contract Comparison identifier and purpose Target types and token/type status Interaction contracts and aligned boundaries Participants, tasks, environments, initial conditions, and timescales Representations and observation models Correspondence mapping and mapping evidence Required invariants and permitted variants Admissible and prohibited transformations Comparison dimensions Formal predicates, metrics, scales, and parameters Weights and aggregation model, if any Equivalence tolerances and decision rules Missingness and uncertainty budget Sensitivity analyses Evidence level for each claim Validity domain and prohibited generalizations Final typed profile: equivalent, approximately equivalent, different, unknown, or incomparable by dimension ## Transfer Contract Source: `02_Research_Papers/.../Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx` Extraction heading: `B. Transfer Contract` ### B. Transfer Contract Identity: source and target episode identifiers, boundaries, timescales, participants, and tasks. Source learning: experience component changed, evidence, magnitude, and uncertainty. Target shift: changed and preserved dimensions across semantic, structural, representational, opportunity, modality, device, social, and temporal axes. Carrier: knowledge, procedure, strategy, belief, value, habit, attunement, artifact, or coordination practice. Mechanism: retrieval, analogy, shared production, policy reuse, cueing, abstraction, compilation, or participation transformation. Outcome: direct measures, derived metrics, latent estimates, direction, durability, and heterogeneity. Counterfactual: control condition and assumptions supporting source attribution. Failure conditions: no source learning, no retention, access failure, mismatch, negative transfer, confounding, or measurement non-invariance. ## Strategy Contract Source: `02_Research_Papers/.../Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx` Extraction heading: `C. Strategy Contract` ### C. Strategy Contract Declared domain and attribution level Episode boundaries and timescale Criteria and constraints State and observation model State abstraction or belief model Opportunity assumptions Action and skill repertoire Conditional selection policy Information-acquisition policy Commitment and persistence rules Contingency and recovery rules Switching and stopping conditions Resource and authority assumptions Expected outcomes and risks Identity invariants under adaptation Evidence and rival strategies Uncertainty and validity domain ## Prediction Contract Source: `02_Research_Papers/.../Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx` Extraction heading: `A. Prediction Contract` ### A. Prediction Contract | Field | Required declaration | | --- | --- | | Identity | Prediction identifier, version, date, owner, intended scientific or operational use. | | Target | Outcome, unit, level, horizon, event definition, censoring, competing events. | | Information cutoff | Timestamp or episode boundary beyond which no input may be used. | | Inputs | Observed records, derived variables, latent estimates, provenance, measurement uncertainty. | | Interaction scope | Participants, episode boundaries, system state, projection, opportunity, policy, context. | | Model | Family, parameters, priors, regularization, training procedure, update rule. | | Causal status | Associational, interventional, transported, mechanism-based, or policy-value claim. | | Prediction form | Probability, distribution, interval, set, hazard, sequence, ranking, or scenario. | | Uncertainty | Aleatoric, epistemic, measurement, state, structural, distributional, reflexive. | | Evaluation | Baselines, holdout design, metrics, calibration, coverage, utility, subgroup tests. | | Validity domain | Population, task, projection, modality, system, policy, environment, time. | | Transport conditions | Assumptions and evidence required for use outside the evaluation domain. | | Failure conditions | Minimum gain, maximum error, calibration tolerance, abstention rule, stop-use conditions. | | Monitoring | Drift tests, recalibration schedule, update triggers, audit trail. | ## Comparison Contract Source: `02_Research_Papers/.../Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx` Extraction heading: `18. Reusable Artifact A - Comparison Contract` ### 18. Reusable Artifact A - Comparison Contract | Field | Required declaration | | --- | --- | | Identity | Candidate interactions; versions; provenance; token or type comparison. | | Reference frame | Target, task, users/agents, context, initial state, boundary, timescale, completion. | | Correspondence | Entities, states, actions, events, outcomes, strategies, measures; ambiguous and unmapped items. | | Invariants | Properties required to remain fixed by dimension. | | Transformations | Renaming, reordering, abstraction, modality substitution, temporal rescaling, implementation substitution. | | Dimensions | Selected comparison dimensions and reasons for inclusion or exclusion. | | Measures | Measurands, instruments, scales, estimators, directionality, reliability, validity. | | Thresholds | Equivalence bounds, minimum acceptable values, smallest effects of interest, vetoes. | | Uncertainty | Record, mapping, sampling, model, instrument, and transport uncertainty. | | Evidence | Formal proofs, records, experiments, qualitative evidence, standards conformance, expert review. | | Decision synthesis | Optional weights, priorities, compensation, authority, sensitivity analysis. | | Scope | Population, task, projection, context, time horizon, and invalidating conditions. | ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/05_Specifications/Contracts/Contract_ID_Registry.md (34 lines, 2.3 KiB) ======================================================================== # Contract ID Registry **Status:** candidate · **Supersedes:** the single shared family identifier `COMPINT-CONTRACT-001`. Each normative contract type now has a **unique, stable identifier**. The former shared identifier `COMPINT-CONTRACT-001` is retained as a **deprecated family alias** that resolves to the whole set below, so existing references and historical artifacts stay resolvable. New references **must** use a specific per-type ID; ambiguous new use of the family alias is deprecated. Version lives in metadata, not in the stable ID (see the canonical namespace plan, C1.6). ## Per-type identifiers | Contract ID | Contract type | Schema (`docs/04_Reference/Templates/`) | Status | |---|---|---|---| | `COMPINT-CONTRACT-PROJECTION-001` | Projection | `Projection_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-OPPORTUNITY-001` | Opportunity | `Opportunity_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-INTERACTION-001` | Interaction | `Interaction_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-BEHAVIORAL-EVIDENCE-001` | Behavioral Evidence | `Behavioral_Evidence_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-MEASUREMENT-001` | Measurement | `Measurement_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-SIMILARITY-001` | Similarity | `Similarity_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-TRANSFER-001` | Transfer | `Transfer_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-STRATEGY-001` | Strategy | `Strategy_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-PREDICTION-001` | Prediction | `Prediction_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-COMPARISON-001` | Comparison | `Comparison_Contract.schema.json` | candidate | | `COMPINT-CONTRACT-COMMON-001` | Common base (shared metadata/lifecycle; the `ContractEnvelope` precursor, C1.10) | `Contract_Common.schema.json` | candidate | ## Deprecated family alias (migration) | Alias | Resolves to | Since | Planned removal | |---|---|---|---| | `COMPINT-CONTRACT-001` | all `COMPINT-CONTRACT-*-001` above | map v0.1.0 | on canonical namespace ratification (C1.6) | Rules: the alias remains resolvable for provenance; it must not be used to introduce new ambiguous references; a reference that could match more than one per-type ID is invalid and must name the type. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/06_Graph/PAPER_DEPENDENCY_EDGES.csv (16 lines, 2.3 KiB) ======================================================================== from,to,relation Interaction_as_a_Scientific_Explanandum,Can_Interaction_Become_a_Primary_Scientific_Object,depends_on_preceding_foundation Can_Interaction_Become_a_Primary_Scientific_Object,How_Sciences_Define_Their_Objects,depends_on_preceding_foundation How_Sciences_Define_Their_Objects,Representation_Invariance_and_Projection,depends_on_preceding_foundation Representation_Invariance_and_Projection,Ontology_Semantics_Representation_and_Interpretation,depends_on_preceding_foundation Ontology_Semantics_Representation_and_Interpretation,Opportunity_Affordance_and_Action_Availability,depends_on_preceding_foundation Opportunity_Affordance_and_Action_Availability,Interaction_Toward_a_General_Theory_of_Interaction,depends_on_preceding_foundation Interaction_Toward_a_General_Theory_of_Interaction,Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior,depends_on_preceding_foundation Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior,Measurement_Toward_a_Scientific_Framework_for_Interaction_Research,depends_on_preceding_foundation Measurement_Toward_a_Scientific_Framework_for_Interaction_Research,Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions,depends_on_preceding_foundation Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions,Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation,depends_on_preceding_foundation Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation,Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization,depends_on_preceding_foundation Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization,Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation,depends_on_preceding_foundation Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation,Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction,depends_on_preceding_foundation Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction,Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions,depends_on_preceding_foundation Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions,Computational_Interaction_Science_Foundations,depends_on_preceding_foundation ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/06_Graph/PAPER_DEPENDENCY_NODES.csv (17 lines, 2.0 KiB) ======================================================================== order,stage,paper_stem,canonical_folder 1,01_Scientific_Explanandum,Interaction_as_a_Scientific_Explanandum,02_Research_Papers/01_Scientific_Explanandum 2,02_Primary_Scientific_Object,Can_Interaction_Become_a_Primary_Scientific_Object,02_Research_Papers/02_Primary_Scientific_Object 3,03_Architecture_of_Sciences,How_Sciences_Define_Their_Objects,02_Research_Papers/03_Architecture_of_Sciences 4,04_Representation_and_Projection,Representation_Invariance_and_Projection,02_Research_Papers/04_Representation_and_Projection 5,05_Ontology_Semantics_Interpretation,Ontology_Semantics_Representation_and_Interpretation,02_Research_Papers/05_Ontology_Semantics_Interpretation 6,06_Opportunity,Opportunity_Affordance_and_Action_Availability,02_Research_Papers/06_Opportunity 7,07_Interaction,Interaction_Toward_a_General_Theory_of_Interaction,02_Research_Papers/07_Interaction 8,08_Behavior,Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior,02_Research_Papers/08_Behavior 9,09_Measurement,Measurement_Toward_a_Scientific_Framework_for_Interaction_Research,02_Research_Papers/09_Measurement 10,10_Similarity,Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions,02_Research_Papers/10_Similarity 11,11_Transfer,Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation,02_Research_Papers/11_Transfer 12,12_Strategies,Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization,02_Research_Papers/12_Strategies 13,13_Formal_Models,Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation,02_Research_Papers/13_Formal_Models 14,14_Prediction,Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction,02_Research_Papers/14_Prediction 15,15_Comparative_Interaction,Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions,02_Research_Papers/15_Comparative_Interaction 16,16_Program_Synthesis,Computational_Interaction_Science_Foundations,02_Research_Papers/16_Program_Synthesis ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/07_Reviews/Computational_Interaction_Science_Wikipedia_Readiness_Review_v0.2.md (33 lines, 2.8 KiB) ======================================================================== # Wikipedia Readiness Review: Foundations of Computational Interaction ## Decision The article should remain a canonical encyclopedia-style project document, not a Wikipedia mainspace submission. Wikipedia's general notability guideline requires significant coverage in reliable sources that are independent of the subject. The exact term *Foundations of Computational Interaction* does not presently appear to have such coverage. Project papers, Fundamental documentation, personal websites, and statements by Zachary Shallbetter are primary or affiliated sources and cannot establish notability. ## Current canonical status The internal project article has advanced through completed work on strict interaction episodes, behavior and trace evidence, measurement, typed similarity, and strategy. These advances strengthen the project corpus but do not change Wikipedia notability because they remain project-authored or affiliated research. ## Updates made The revised article describes FCI as a proposed research program, avoids claims that it is established or proven, gives substantial space to adjacent disciplines, adds criticism and unresolved questions, separates project-documented provenance from independent public history, and treats formulas as proposed analytical models rather than accepted scientific laws. ## Conflict of interest Zachary Shallbetter has a direct professional and intellectual connection to the topic. Wikipedia recommends that connected editors avoid creating the article directly. A future submission should disclose the relationship and use the Articles for Creation review process. ## What would establish notability A standalone article would require multiple independent secondary sources discussing FCI itself in depth. Suitable evidence could include peer-reviewed papers by unaffiliated researchers, scholarly books or chapters, independent journal or conference reviews, substantial reporting by reputable publications, or independent adoption and criticism of the terminology and framework. Citations to Gibson, Norman, Shannon, Suchman, Hacking, Hutchins, and related scholarship support the discussion of neighboring ideas. They do not establish the notability of FCI. ## Attribution of coinage The canonical project history may state that the term was introduced by Zachary Shallbetter during the development of Fundamental. A Wikipedia article should include that claim only after an independent reliable source attributes the coinage. ## AI-generated text Wikipedia's current first-article guidance advises contributors not to use large language models to generate article content. This draft should therefore be treated as research and editorial preparation. A human editor would need to verify every claim and source, rewrite or independently edit the text, disclose any conflict of interest, and accept responsibility for the final submission. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Glossary.md (2154 lines, 81.2 KiB) ======================================================================== **Canonical Glossary** *Reconciled Computational Interaction Science vocabulary* Version 1.0.0-integration.1 # Governance This document owns reconciled canonical wording for the integration release. It does not introduce new theory. Source papers remain provenance and evidence. # Domain commitments A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology. **Boundary:** Domain commitments specify what the model admits. They do not by themselves assign meaning, produce a representation, or determine interpretation. ----------------------------------------------------------------------- Canonical ID domain-commitments ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases ontology commitments Deprecated None Dependencies None Originating paper Ontology, Semantics, Representation, and Interpretation Supporting papers Ontology, Semantics, Representation, and Interpretation; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT? Contracts None ----------------------------------------------------------------------- # System state The physical, computational, social, or modeled condition of a declared system at a particular time. **Boundary:** State is not synonymous with data, meaning, representation, or observation. A state becomes content-bearing only under a specified semantics. ----------------------------------------------------------------------- Canonical ID system-state ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases state Deprecated None Dependencies Domain commitments, State transition Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Ontology, Semantics, Representation, and Interpretation; Interaction; Interaction Strategies; Predicting Interaction Contracts Projection Contract, Opportunity Contract, Interaction Contract, Behavioral Evidence Contract, Measurement Contract, Similarity Contract, Transfer Contract, Strategy Contract, Prediction Contract ----------------------------------------------------------------------- # Semantic assignment A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain. **Boundary:** Formal semantic assignment is distinct from a person's interpretation or understanding. ----------------------------------------------------------------------- Canonical ID semantic-assignment ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases formal semantics Deprecated None Dependencies Domain commitments Originating paper Ontology, Semantics, Representation, and Interpretation Supporting papers Ontology, Semantics, Representation, and Interpretation Contracts None ----------------------------------------------------------------------- # Semantic state The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state. **Boundary:** No observer-independent semantic state is assumed without an explicit theory and scope. ----------------------------------------------------------------------- Canonical ID semantic-state ----------------------------------- ----------------------------------- Maturity Proposed Observable No - latent/inferred Latent Yes Measurement Requires latent-variable model Aliases None Deprecated None Dependencies Semantic assignment Originating paper Ontology, Semantics, Representation, and Interpretation Supporting papers Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; Computational Interaction Science Contracts None ----------------------------------------------------------------------- # Information A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use. **Boundary:** Information is not a synonym for stored variables, data, meaning, semantic state, or interpretation. Every claim that information is preserved must name the information theory, source, code, task, or relevance criterion. ----------------------------------------------------------------------- Canonical ID information ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Ontology, Semantics, Representation, and Interpretation Supporting papers Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; Interaction Strategies; Predicting Interaction; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Contracts None ----------------------------------------------------------------------- # Representation A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice.\ \ A representation may preserve, transform, omit, or introduce structure. **Boundary:** A representation is not identical with its target. Equal reference does not imply semantic, inferential, behavioral, or interactional equivalence. ----------------------------------------------------------------------- Canonical ID representation ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases representational vehicle Deprecated None Dependencies Projection Originating paper Representation, Invariance, and Projection Supporting papers Representation, Invariance, and Projection; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Ontology, Semantics, Representation, and Interpretation; Interaction Transfer; Computational Interaction Science Contracts None ----------------------------------------------------------------------- **Example:** A table and graph that selectively expose the same declared target. **Counterexample:** The target itself, treated as identical with its representation. # Projection A declared transformation from a target description, system state, or semantic assignment into an accessible representational form.\ \ A projection contract specifies:\ \ - target and authority;\ - mapping or construction rule;\ - interpretation assumptions;\ - preserved properties;\ - transformed properties;\ - omitted properties;\ - introduced properties;\ - available operations;\ - observer assumptions;\ - intended use;\ - context and scope;\ - uncertainty, tolerance, and failure conditions. **Boundary:** Projection coordinates established concepts such as views, abstractions, encodings, lenses, simulations, model morphisms, and renderings. It is not a new metaphysical substance. ----------------------------------------------------------------------- Canonical ID projection ----------------------------------- ----------------------------------- Maturity Proposed analytical role Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases view, encoding, rendering Deprecated None Dependencies System state, Semantic assignment Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Representation, Invariance, and Projection; Formal Models of Computational Interaction; Computational Interaction Science; Predicting Interaction Contracts Projection Contract ----------------------------------------------------------------------- **Example:** A declared mapping from a system state to a GUI, API, or auditory form. **Counterexample:** An implementation artifact with no declared target, mapping, or scope. # Scoped invariance A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance.\ \ Invariance must be typed. Relevant types include:\ \ - ontological;\ - semantic;\ - informational;\ - structural;\ - topological;\ - computational;\ - inferential;\ - task;\ - behavioral;\ - interactional. **Boundary:** No one invariance type implies another. ----------------------------------------------------------------------- Canonical ID scoped-invariance ----------------------------------- ----------------------------------- Maturity Proposed theory Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated semantic invariance Dependencies Projection, Equivalence Originating paper Canonical glossary Supporting papers None Contracts None ----------------------------------------------------------------------- # Interpretation The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose. **Boundary:** Interpretation is a process or event. Semantics specifies or stabilizes admissible relations; interpretation applies or revises them. ----------------------------------------------------------------------- Canonical ID interpretation ----------------------------------- ----------------------------------- Maturity Proposed Observable No - latent/inferred Latent Yes Measurement Requires latent-variable model Aliases None Deprecated None Dependencies Representation, Interaction history Originating paper Ontology, Semantics, Representation, and Interpretation Supporting papers Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Measurement; Computational Interaction Science Contracts None ----------------------------------------------------------------------- **Example:** An agent applies conventions and context to a signaled operation. **Counterexample:** Formal semantics treated as identical to a participant's understanding. # Interaction participant Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction.\ \ A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning. **Boundary:** Interaction participant is the top-level role. More specific terms such as human participant, computational participant, institution, observer, mediator, autonomous agent, and AI agent should be used when their additional commitments matter. ----------------------------------------------------------------------- Canonical ID interaction-participant ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases participant Deprecated None Dependencies Agent Originating paper Canonical glossary Supporting papers None Contracts Interaction Contract ----------------------------------------------------------------------- # Agent An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization. **Boundary:** Agent is not the universal term for every participant. An AI model is not automatically an agent; it becomes part of an agentic system when observations, action-selection, and consequential operations are supplied. ----------------------------------------------------------------------- Canonical ID agent ----------------------------------- ----------------------------------- Maturity Proposed subtype Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Interaction; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Formal Models of Computational Interaction; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Contracts None ----------------------------------------------------------------------- # Environment The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur. **Boundary:** The environment is not identical with what an agent can observe through a representation. ----------------------------------------------------------------------- Canonical ID environment ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Behavior Supporting papers Behavior; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Interaction; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Ontology, Semantics, Representation, and Interpretation Contracts None ----------------------------------------------------------------------- # Affordance An action-relevant relation between an agent's effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist. **Boundary:** Affordance is not synonymous with permission, signaling, belief, execution success, or reversibility. ----------------------------------------------------------------------- Canonical ID affordance ----------------------------------- ----------------------------------- Maturity Established external construct Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated perceived affordance Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Representation, Invariance, and Projection; Ontology, Semantics, Representation, and Interpretation; Predicting Interaction Contracts None ----------------------------------------------------------------------- # Opportunity A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions.\ \ Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty. ----------------------------------------------------------------------- Canonical ID opportunity ----------------------------------- ----------------------------------- Maturity Proposed coordination framework Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated opportunity as a primitive Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Interaction Similarity; Interaction Strategies; Computational Interaction Science; Predicting Interaction Contracts Opportunity Contract ----------------------------------------------------------------------- # Opportunity profile For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations:\ \ - domain-valid;\ - effectively capable;\ - permitted;\ - enabled;\ - reachable outcomes;\ - exposed;\ - signaled;\ - believed available;\ - expected consequences;\ - selected;\ - executed;\ - successful;\ - reversible or recoverable;\ - uncertainty and provenance.\ \ Selected, executed, and successful are trace predicates rather than availability sets. ----------------------------------------------------------------------- Canonical ID opportunity-profile ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases typed opportunity profile Deprecated opportunity as a primitive Dependencies Interpretation, System state, Projection, Affordance, Capability, Permission, Enablement, Reachability, Exposure, Signaling, Believed action Originating paper Representation, Invariance, and Projection Supporting papers Representation, Invariance, and Projection; Opportunity, Affordance, and Action Availability; Behavior; Interaction Similarity; Interaction Strategies Contracts Opportunity Contract ----------------------------------------------------------------------- **Example:** A profile distinguishing permitted, enabled, exposed, signaled, and believed actions. **Counterexample:** A visible control treated as proof that an action is feasible or believed. # Capability The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions. **Boundary:** Capability is distinct from permission. Security capability tokens must be named explicitly when that narrower meaning is intended. ----------------------------------------------------------------------- Canonical ID capability ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Computational Interaction Science; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Interaction Contracts None ----------------------------------------------------------------------- # Permission Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation. **Boundary:** A prohibited action may remain technically possible. ----------------------------------------------------------------------- Canonical ID permission ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Computational Interaction Science; Behavior; Interaction Similarity; Interaction Strategies Contracts None ----------------------------------------------------------------------- # Enablement The condition in which an action's current-state preconditions are satisfied. **Boundary:** Enablement is local to the current state and differs from multi-step reachability. ----------------------------------------------------------------------- Canonical ID enablement ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases enabled action Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction Contracts None ----------------------------------------------------------------------- # Reachability The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon. ----------------------------------------------------------------------- Canonical ID reachability ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases None Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction; Interaction Contracts None ----------------------------------------------------------------------- # Exposure Provision by the current projection of an executable access path to an operation. **Boundary:** An exposed operation may be hidden, poorly signaled, unknown, or inaccessible to a particular observer. ----------------------------------------------------------------------- Canonical ID exposure ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases operation exposure Deprecated None Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Interaction Transfer; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Predicting Interaction; Formal Models of Computational Interaction Contracts None ----------------------------------------------------------------------- # Signaling Perceivable information indicating an operation, condition, consequence, state, or recovery path. **Boundary:** A signal may be true, incomplete, ambiguous, or false. ----------------------------------------------------------------------- Canonical ID signaling ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases signifier Deprecated perceived affordance Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Computational Interaction Science; Formal Models of Computational Interaction; Predicting Interaction; Comparative Interaction Contracts None ----------------------------------------------------------------------- # Discoverability The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions. **Boundary:** Discoverability is not a static visual property. ----------------------------------------------------------------------- Canonical ID discoverability ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases None Deprecated perceived affordance Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; Measurement; Representation, Invariance, and Projection; Interaction Transfer; Comparative Interaction Contracts None ----------------------------------------------------------------------- # Believed action An action represented by an agent as available, with an associated confidence and expected consequence. **Boundary:** Belief cannot be read directly from non-selection or task completion. It requires elicitation or a validated inferential model. ----------------------------------------------------------------------- Canonical ID believed-action ----------------------------------- ----------------------------------- Maturity Proposed latent variable Observable No - latent/inferred Latent Yes Measurement Requires latent-variable model Aliases believed availability Deprecated perceived affordance Dependencies Interaction history Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Interaction Similarity; Interaction Transfer; Predicting Interaction Contracts None ----------------------------------------------------------------------- # Action A declared intervention, command, operation, or behavior capable of participating in a state transition. **Boundary:** A low-level input such as a click or touch is not necessarily the semantic action under study. ----------------------------------------------------------------------- Canonical ID action ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated perceived affordance, interaction causes behavior Dependencies None Originating paper Opportunity, Affordance, and Action Availability Supporting papers Opportunity, Affordance, and Action Availability; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Interaction Strategies; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Behavior Contracts Interaction Contract ----------------------------------------------------------------------- # State transition A change from one declared system state to another under a transition relation, process, or event. ----------------------------------------------------------------------- Canonical ID state-transition ----------------------------------- ----------------------------------- Maturity Proposed Observable Directly/Instrumentally Latent No or not inherently Measurement Measure only under declared operationalization Aliases transition Deprecated None Dependencies Action Originating paper Interaction Supporting papers Interaction; Behavior; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT? Contracts None ----------------------------------------------------------------------- # Observation A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process. **Boundary:** Observation is not interpretation, inference, or evidence by itself. ----------------------------------------------------------------------- Canonical ID observation ----------------------------------- ----------------------------------- Maturity Proposed Observable Directly/Instrumentally Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Formal Models of Computational Interaction Supporting papers Formal Models of Computational Interaction; Measurement; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Interaction Strategies; Interaction Similarity Contracts Projection Contract, Opportunity Contract, Interaction Contract, Behavioral Evidence Contract, Measurement Contract, Similarity Contract, Transfer Contract, Strategy Contract, Prediction Contract ----------------------------------------------------------------------- # Situated behavior A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model. **Boundary:** Representation does not determine behavior directly. ----------------------------------------------------------------------- Canonical ID situated-behavior ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Canonical glossary Supporting papers None Contracts None ----------------------------------------------------------------------- # Behavioral evidence A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim. **Boundary:** A trace is evidence of what occurred. It is not direct evidence of intention, understanding, culture, personality, or protected identity. ----------------------------------------------------------------------- Canonical ID behavioral-evidence ----------------------------------- ----------------------------------- Maturity Candidate Observable Directly/Instrumentally Latent No or not inherently Measurement Measure only under declared operationalization Aliases behavior evidence Deprecated None Dependencies Measurement contract Originating paper Behavior Supporting papers Behavior; Computational Interaction Science; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Formal Models of Computational Interaction; Comparative Interaction Contracts Behavioral Evidence Contract ----------------------------------------------------------------------- # Behavioral equivalence Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance. **Boundary:** Behavioral equivalence does not imply semantic, interpretive, strategy, learning, transfer, or interactional equivalence. ----------------------------------------------------------------------- Canonical ID behavioral-equivalence ----------------------------------- ----------------------------------- Maturity Candidate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Representation, Invariance, and Projection Supporting papers Representation, Invariance, and Projection; Interaction Similarity; Formal Models of Computational Interaction; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability Contracts Behavioral Evidence Contract ----------------------------------------------------------------------- # Interactional equivalence Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions. ----------------------------------------------------------------------- Canonical ID interactional-equivalence ----------------------------------- ----------------------------------- Maturity Candidate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Supporting papers INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Representation, Invariance, and Projection; Interaction Similarity Contracts None ----------------------------------------------------------------------- # Interaction A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence. **Boundary:** Interaction is not reducible to action, behavior, communication, computation, observation, state transition, feedback, or causation alone. Ordinary-language usage may be broader than the strict research definition. ----------------------------------------------------------------------- Canonical ID interaction ----------------------------------- ----------------------------------- Maturity Proposed scientific target Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated interaction causes behavior Dependencies Computational Interaction Science Originating paper Interaction Supporting papers Interaction; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Computational Interaction Science; Predicting Interaction Contracts Interaction Contract ----------------------------------------------------------------------- # Interaction episode A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale.\ \ Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated. **Boundary:** A single isolated one-way causal effect is not an interaction episode under the strict definition unless it enters a recurrent or reciprocally constraining structure. ----------------------------------------------------------------------- Canonical ID interaction-episode ----------------------------------- ----------------------------------- Maturity Proposed canonical unit Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases strict interaction episode Deprecated None Dependencies Opportunity profile, Coupling, Token identity, Type identity, Interaction contract Originating paper Interaction Supporting papers Interaction; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Formal Models of Computational Interaction; Computational Interaction Science; Predicting Interaction Contracts Interaction Contract ----------------------------------------------------------------------- **Example:** A request, response, and later state-dependent continuation within a declared protocol boundary. **Counterexample:** A one-way message with no reciprocal or recurrent constraint inside the declared episode. # Coupling A relation or pathway through which a participant or shared medium can alter another participant\'s transition structure, reachable states, probabilities, timing, or constraints. ----------------------------------------------------------------------- Canonical ID coupling ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies Interaction participant, Environment Originating paper Interaction Supporting papers Interaction; CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Formal Models of Computational Interaction; How Sciences Define Their Objects Contracts None ----------------------------------------------------------------------- # Perturbation A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes. ----------------------------------------------------------------------- Canonical ID perturbation ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Supporting papers Interaction; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Contracts None ----------------------------------------------------------------------- # Uptake Incorporation of a perturbation into a participant\'s state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious. ----------------------------------------------------------------------- Canonical ID uptake ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Supporting papers Interaction; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability Contracts None ----------------------------------------------------------------------- # Recurrence Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration. ----------------------------------------------------------------------- Canonical ID recurrence ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Supporting papers Interaction; Interaction Strategies; Behavior Contracts None ----------------------------------------------------------------------- # Interaction contract A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions. ----------------------------------------------------------------------- Canonical ID interaction-contract ----------------------------------- ----------------------------------- Maturity Proposed reusable artifact Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Supporting papers Interaction; Computational Interaction Science; Comparative Interaction Contracts Interaction Contract ----------------------------------------------------------------------- # Interaction morphology The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality. **Boundary:** Morphology is not independent of all semantics or interpretation. A study must declare which content and operations are controlled. ----------------------------------------------------------------------- Canonical ID interaction-morphology ----------------------------------- ----------------------------------- Maturity Candidate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Canonical glossary Supporting papers None Contracts Interaction Contract ----------------------------------------------------------------------- # Interaction grammar A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation. ----------------------------------------------------------------------- Canonical ID interaction-grammar ----------------------------------- ----------------------------------- Maturity Candidate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT? Supporting papers CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; Interaction Contracts Interaction Contract ----------------------------------------------------------------------- # Interaction history The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent's later beliefs, policies, and interpretation. **Boundary:** Interaction history biases later behavior but does not fully explain or determine an individual. ----------------------------------------------------------------------- Canonical ID interaction-history ----------------------------------- ----------------------------------- Maturity Candidate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Supporting papers INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Contracts Interaction Contract ----------------------------------------------------------------------- # Trace A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules. **Boundary:** A trace is not identical with behavior, action, policy, strategy, intention, or mechanism. ----------------------------------------------------------------------- Canonical ID trace ----------------------------------- ----------------------------------- Maturity Proposed Observable Directly/Instrumentally Latent No or not inherently Measurement Operationalizable by contract Aliases interaction trace, behavioral trace Deprecated None Dependencies Observation Originating paper Interaction Similarity Supporting papers Interaction Similarity; Behavior; Interaction Strategies; Interaction; Predicting Interaction Contracts Projection Contract, Opportunity Contract, Interaction Contract, Behavioral Evidence Contract, Measurement Contract, Similarity Contract, Transfer Contract, Strategy Contract, Prediction Contract ----------------------------------------------------------------------- # Measurement contract A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation. **Boundary:** A metric is not a construct. Numerical output does not justify a latent interpretation without a validated measurement relation. ----------------------------------------------------------------------- Canonical ID measurement-contract ----------------------------------- ----------------------------------- Maturity Proposed reusable artifact Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases None Deprecated None Dependencies Trace Originating paper Measurement Supporting papers Measurement; Formal Models of Computational Interaction; Computational Interaction Science; Behavior; Interaction Transfer Contracts Measurement Contract ----------------------------------------------------------------------- **Example:** A declaration of measurand, observation process, scale, uncertainty, and admissible inference. **Counterexample:** A response-time column treated as a construct without validity conditions. # Interaction similarity A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain. **Boundary:** There is no context-free universal similarity score. ----------------------------------------------------------------------- Canonical ID interaction-similarity ----------------------------------- ----------------------------------- Maturity Proposed typed comparison framework Observable Conditional on observation model Latent No or not inherently Measurement Operationalizable by contract Aliases None Deprecated None Dependencies Measurement contract, Similarity contract Originating paper INTERACTION AS A\ SCIENTIFIC EXPLANANDUM Supporting papers INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Interaction Similarity; Predicting Interaction; Comparative Interaction; Computational Interaction Science Contracts Interaction Contract ----------------------------------------------------------------------- **Example:** A typed profile comparing protocol, opportunity, trace, and outcome dimensions. **Counterexample:** One aggregate score presented without a comparison contract. # Token identity Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria. ----------------------------------------------------------------------- Canonical ID token-identity ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Supporting papers Interaction; Interaction Similarity; Comparative Interaction Contracts None ----------------------------------------------------------------------- # Type identity Membership in the same abstraction-defined interaction class under explicit classification rules. ----------------------------------------------------------------------- Canonical ID type-identity ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Similarity Supporting papers Interaction Similarity; Interaction; Comparative Interaction Contracts None ----------------------------------------------------------------------- # Equivalence Exact preservation under a declared comparison contract and observable set. Equivalence is always typed. ----------------------------------------------------------------------- Canonical ID equivalence ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases typed equivalence Deprecated None Dependencies Interaction similarity Originating paper Interaction Similarity Supporting papers Interaction Similarity; Representation, Invariance, and Projection; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Comparative Interaction; Formal Models of Computational Interaction Contracts None ----------------------------------------------------------------------- # Similarity Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty. ----------------------------------------------------------------------- Canonical ID similarity ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases typed similarity Deprecated universal similarity score Dependencies None Originating paper Interaction Similarity Supporting papers Interaction Similarity; INTERACTION AS A\ SCIENTIFIC EXPLANANDUM; Computational Interaction Science; Interaction Transfer; Predicting Interaction Contracts Similarity Contract ----------------------------------------------------------------------- # Incomparability Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions. ----------------------------------------------------------------------- Canonical ID incomparability ----------------------------------- ----------------------------------- Maturity Proposed Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Comparative Interaction Supporting papers Comparative Interaction; Interaction Similarity; Computational Interaction Science Contracts None ----------------------------------------------------------------------- # Similarity contract A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile. ----------------------------------------------------------------------- Canonical ID similarity-contract ----------------------------------- ----------------------------------- Maturity Proposed reusable artifact Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Similarity Supporting papers Interaction Similarity; Predicting Interaction Contracts Similarity Contract ----------------------------------------------------------------------- # Strategy An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states. **Boundary:** A strategy is not a single action, raw trace, repeated sequence, explicit plan, policy alone, skill, habit, or intention. It must be supported through rival discrimination, diagnostic contingencies, uncertainty, and evidence appropriate to the claim. ----------------------------------------------------------------------- Canonical ID strategy ----------------------------------- ----------------------------------- Maturity Proposed latent explanatory construct Observable No - latent/inferred Latent Yes Measurement Requires latent-variable model Aliases None Deprecated None Dependencies Policy, Interaction history, Strategy contract Originating paper Interaction Strategies Supporting papers Interaction Strategies; Predicting Interaction; Interaction Transfer; Formal Models of Computational Interaction; Computational Interaction Science Contracts Strategy Contract ----------------------------------------------------------------------- **Example:** An inferred pattern of conditional search, commitment, and recovery across episodes. **Counterexample:** A single successful action labeled as a strategy. # Strategy contract A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain. ----------------------------------------------------------------------- Canonical ID strategy-contract ----------------------------------- ----------------------------------- Maturity Proposed reusable artifact Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper Interaction Strategies Supporting papers Interaction Strategies Contracts Strategy Contract ----------------------------------------------------------------------- # Policy A conditional relation from represented states, observations, or beliefs to action distributions. **Boundary:** A policy may be one component of a strategy. Strategy may additionally include information acquisition, commitment, resource allocation, switching, recovery, and stopping rules. ----------------------------------------------------------------------- Canonical ID policy ----------------------------------- ----------------------------------- Maturity Proposed Observable No - latent/inferred Latent Yes Measurement Requires latent-variable model Aliases None Deprecated None Dependencies None Originating paper Interaction Strategies Supporting papers Interaction Strategies; Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction; Behavior; Interaction Similarity Contracts None ----------------------------------------------------------------------- # Fundamental A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected. **Boundary:** Fundamental is not the scientific theory, a philosophical ontology, proof of CIS, or a guarantee of shared human meaning. ----------------------------------------------------------------------- Canonical ID fundamental ----------------------------------- ----------------------------------- Maturity Proposed research substrate Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases None Deprecated None Dependencies None Originating paper CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT? Supporting papers CAN INTERACTION BECOME A\ PRIMARY SCIENTIFIC OBJECT?; How Sciences Define Their Objects; Representation, Invariance, and Projection; Predicting Interaction Contracts None ----------------------------------------------------------------------- # Computational Interaction Science A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence.\ \ CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines. ----------------------------------------------------------------------- Canonical ID computational-interaction-science ----------------------------------- ----------------------------------- Maturity Proposed research program; disciplinary autonomy unproven Observable Conditional on observation model Latent No or not inherently Measurement Measure only under declared operationalization Aliases CompInt Deprecated None Dependencies None Originating paper Computational Interaction Science Supporting papers Computational Interaction Science; Predicting Interaction Contracts None ----------------------------------------------------------------------- ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/08_Canonical_Registry/Canonical_Ontology.md (789 lines, 23.1 KiB) ======================================================================== **Canonical Ontology** *Relational ontology and contract stack* Version 1.0.0-integration.1 # Scope This ontology reconciles the Version 1.0 relational architecture. It is a dependency and evidence architecture, not a universal causal pipeline. # Core commitments - Interaction is not a primitive substance. - Opportunity is a typed coordination framework, not a primitive. - Behavior is attributed under a declared observation model. - Interpretation, belief, policy, and strategy require explicit inferential treatment. - Measurement, equivalence, and similarity are contract-relative. # Concepts ## Domain commitments A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology. **Dependencies:** None **Dependents:** System state, Semantic assignment ## System state The physical, computational, social, or modeled condition of a declared system at a particular time. **Dependencies:** Domain commitments, State transition **Dependents:** Projection, Opportunity profile ## Semantic assignment A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain. **Dependencies:** Domain commitments **Dependents:** Semantic state, Projection ## Semantic state The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state. **Dependencies:** Semantic assignment **Dependents:** None ## Information A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use. **Dependencies:** None **Dependents:** None ## Representation A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice.\ \ A representation may preserve, transform, omit, or introduce structure. **Dependencies:** Projection **Dependents:** Interpretation ## Projection A declared transformation from a target description, system state, or semantic assignment into an accessible representational form.\ \ A projection contract specifies:\ \ - target and authority;\ - mapping or construction rule;\ - interpretation assumptions;\ - preserved properties;\ - transformed properties;\ - omitted properties;\ - introduced properties;\ - available operations;\ - observer assumptions;\ - intended use;\ - context and scope;\ - uncertainty, tolerance, and failure conditions. **Dependencies:** System state, Semantic assignment **Dependents:** Representation, Opportunity profile, Scoped invariance ## Scoped invariance A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance.\ \ Invariance must be typed. Relevant types include:\ \ - ontological;\ - semantic;\ - informational;\ - structural;\ - topological;\ - computational;\ - inferential;\ - task;\ - behavioral;\ - interactional. **Dependencies:** Projection, Equivalence **Dependents:** None ## Interpretation The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose. **Dependencies:** Representation, Interaction history **Dependents:** Opportunity profile ## Interaction participant Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction.\ \ A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning. **Dependencies:** Agent **Dependents:** Coupling ## Agent An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization. **Dependencies:** None **Dependents:** Interaction participant ## Environment The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur. **Dependencies:** None **Dependents:** Coupling ## Affordance An action-relevant relation between an agent's effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist. **Dependencies:** None **Dependents:** Opportunity profile ## Opportunity A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions.\ \ Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty. **Dependencies:** None **Dependents:** None ## Opportunity profile For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations:\ \ - domain-valid;\ - effectively capable;\ - permitted;\ - enabled;\ - reachable outcomes;\ - exposed;\ - signaled;\ - believed available;\ - expected consequences;\ - selected;\ - executed;\ - successful;\ - reversible or recoverable;\ - uncertainty and provenance.\ \ Selected, executed, and successful are trace predicates rather than availability sets. **Dependencies:** Interpretation, System state, Projection, Affordance, Capability, Permission, Enablement, Reachability, Exposure, Signaling, Believed action **Dependents:** Interaction episode ## Capability The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions. **Dependencies:** None **Dependents:** Opportunity profile ## Permission Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation. **Dependencies:** None **Dependents:** Opportunity profile ## Enablement The condition in which an action's current-state preconditions are satisfied. **Dependencies:** None **Dependents:** Opportunity profile ## Reachability The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon. **Dependencies:** None **Dependents:** Opportunity profile ## Exposure Provision by the current projection of an executable access path to an operation. **Dependencies:** None **Dependents:** Opportunity profile ## Signaling Perceivable information indicating an operation, condition, consequence, state, or recovery path. **Dependencies:** None **Dependents:** Opportunity profile ## Discoverability The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions. **Dependencies:** None **Dependents:** None ## Believed action An action represented by an agent as available, with an associated confidence and expected consequence. **Dependencies:** Interaction history **Dependents:** Opportunity profile ## Action A declared intervention, command, operation, or behavior capable of participating in a state transition. **Dependencies:** None **Dependents:** State transition ## State transition A change from one declared system state to another under a transition relation, process, or event. **Dependencies:** Action **Dependents:** System state ## Observation A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process. **Dependencies:** None **Dependents:** Trace ## Situated behavior A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model. **Dependencies:** None **Dependents:** None ## Behavioral evidence A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim. **Dependencies:** Measurement contract **Dependents:** None ## Behavioral equivalence Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance. **Dependencies:** None **Dependents:** None ## Interactional equivalence Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions. **Dependencies:** None **Dependents:** None ## Interaction A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence. **Dependencies:** Computational Interaction Science **Dependents:** None ## Interaction episode A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale.\ \ Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated. **Dependencies:** Opportunity profile, Coupling, Token identity, Type identity, Interaction contract **Dependents:** None ## Coupling A relation or pathway through which a participant or shared medium can alter another participant\'s transition structure, reachable states, probabilities, timing, or constraints. **Dependencies:** Interaction participant, Environment **Dependents:** Interaction episode ## Perturbation A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes. **Dependencies:** None **Dependents:** None ## Uptake Incorporation of a perturbation into a participant\'s state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious. **Dependencies:** None **Dependents:** None ## Recurrence Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration. **Dependencies:** None **Dependents:** None ## Interaction contract A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions. **Dependencies:** None **Dependents:** Interaction episode ## Interaction morphology The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality. **Dependencies:** None **Dependents:** None ## Interaction grammar A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation. **Dependencies:** None **Dependents:** None ## Interaction history The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent's later beliefs, policies, and interpretation. **Dependencies:** None **Dependents:** Strategy, Interpretation, Believed action ## Trace A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules. **Dependencies:** Observation **Dependents:** Measurement contract ## Measurement contract A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation. **Dependencies:** Trace **Dependents:** Interaction similarity, Behavioral evidence ## Interaction similarity A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain. **Dependencies:** Measurement contract, Similarity contract **Dependents:** Equivalence ## Token identity Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria. **Dependencies:** None **Dependents:** Interaction episode ## Type identity Membership in the same abstraction-defined interaction class under explicit classification rules. **Dependencies:** None **Dependents:** Interaction episode ## Equivalence Exact preservation under a declared comparison contract and observable set. Equivalence is always typed. **Dependencies:** Interaction similarity **Dependents:** Scoped invariance ## Similarity Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty. **Dependencies:** None **Dependents:** None ## Incomparability Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions. **Dependencies:** None **Dependents:** None ## Similarity contract A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile. **Dependencies:** None **Dependents:** Interaction similarity ## Strategy An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states. **Dependencies:** Policy, Interaction history, Strategy contract **Dependents:** None ## Strategy contract A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain. **Dependencies:** None **Dependents:** Strategy ## Policy A conditional relation from represented states, observations, or beliefs to action distributions. **Dependencies:** None **Dependents:** Strategy ## Fundamental A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected. **Dependencies:** None **Dependents:** None ## Computational Interaction Science A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence.\ \ CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines. **Dependencies:** None **Dependents:** Interaction # Canonical relations ------------------------------------------------------------------------- **Source** **Relation** **Target** **Authority** ----------------- ----------------- ----------------- ------------------- Domain constrains System state Canonical commitments ontology/glossary Domain constrains Semantic Canonical commitments assignment ontology/glossary Semantic licenses Semantic state Canonical assignment ontology/glossary System state source for Projection Canonical ontology/glossary Semantic source for Projection Canonical assignment ontology/glossary Projection realizes Representation Canonical ontology/glossary Representation supports Interpretation Canonical ontology/glossary Interpretation informs Opportunity Canonical profile ontology/glossary System state constrains Opportunity Canonical profile ontology/glossary Projection exposes Opportunity Canonical profile ontology/glossary Opportunity conditions Interaction Canonical profile episode ontology/glossary Coupling constitutes Interaction Canonical episode ontology/glossary Interaction participates in Coupling Canonical participant ontology/glossary Observation records Trace Canonical ontology/glossary Trace input to Measurement Canonical contract ontology/glossary Measurement supports Interaction Canonical contract similarity ontology/glossary Interaction types Equivalence Canonical similarity ontology/glossary Policy component of Strategy Canonical ontology/glossary Interaction updates Strategy Canonical history ontology/glossary Interaction conditions Interpretation Canonical history ontology/glossary Interaction conditions Believed action Canonical history ontology/glossary Affordance contributes Opportunity Canonical profile ontology/glossary Capability component Opportunity Canonical profile ontology/glossary Permission component Opportunity Canonical profile ontology/glossary Enablement component Opportunity Canonical profile ontology/glossary Reachability component Opportunity Canonical profile ontology/glossary Exposure component Opportunity Canonical profile ontology/glossary Signaling component Opportunity Canonical profile ontology/glossary Believed action component Opportunity Canonical profile ontology/glossary Action may produce State transition Canonical ontology/glossary State transition changes System state Canonical ontology/glossary Agent subtype of Interaction Canonical participant ontology/glossary Environment mediates Coupling Canonical ontology/glossary Token identity identifies Interaction Canonical episode ontology/glossary Type identity classifies Interaction Canonical episode ontology/glossary Similarity specifies Interaction Canonical contract similarity ontology/glossary Strategy contract specifies Strategy Canonical ontology/glossary Interaction specifies Interaction Canonical contract episode ontology/glossary Measurement governs Behavioral Canonical contract evidence ontology/glossary Projection tested across Scoped invariance Canonical ontology/glossary Equivalence expresses Scoped invariance Canonical ontology/glossary Computational studies Interaction Canonical Interaction ontology/glossary Science ------------------------------------------------------------------------- # Contract stack The normative contract wording remains in the consolidated contracts source. The stack includes Projection, Opportunity, Interaction, Behavioral Evidence, Measurement, Similarity, Transfer, Strategy, and Prediction contracts. # Appendix A - Candidate Version 2.0 Changes - Consider whether "Computational Interaction Science" remains the preferred program name after empirical validation; current evidence supports interdisciplinary synthesis rather than disciplinary autonomy. - Consider a formally ratified distinction between broad ordinary-language interaction and the strict interaction-episode research definition. - Evaluate whether transfer should become a first-class ontology node in a future normative revision; it is presently represented primarily through contracts and papers. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Graphs/Knowledge_Graph_Edges.csv (43 lines, 2.9 KiB) ======================================================================== source,target,relation,authority domain-commitments,system-state,constrains,Canonical ontology/glossary domain-commitments,semantic-assignment,constrains,Canonical ontology/glossary semantic-assignment,semantic-state,licenses,Canonical ontology/glossary system-state,projection,source for,Canonical ontology/glossary semantic-assignment,projection,source for,Canonical ontology/glossary projection,representation,realizes,Canonical ontology/glossary representation,interpretation,supports,Canonical ontology/glossary interpretation,opportunity-profile,informs,Canonical ontology/glossary system-state,opportunity-profile,constrains,Canonical ontology/glossary projection,opportunity-profile,exposes,Canonical ontology/glossary opportunity-profile,interaction-episode,conditions,Canonical ontology/glossary coupling,interaction-episode,constitutes,Canonical ontology/glossary interaction-participant,coupling,participates in,Canonical ontology/glossary observation,trace,records,Canonical ontology/glossary trace,measurement-contract,input to,Canonical ontology/glossary measurement-contract,interaction-similarity,supports,Canonical ontology/glossary interaction-similarity,equivalence,types,Canonical ontology/glossary policy,strategy,component of,Canonical ontology/glossary interaction-history,strategy,updates,Canonical ontology/glossary interaction-history,interpretation,conditions,Canonical ontology/glossary interaction-history,believed-action,conditions,Canonical ontology/glossary affordance,opportunity-profile,contributes,Canonical ontology/glossary capability,opportunity-profile,component,Canonical ontology/glossary permission,opportunity-profile,component,Canonical ontology/glossary enablement,opportunity-profile,component,Canonical ontology/glossary reachability,opportunity-profile,component,Canonical ontology/glossary exposure,opportunity-profile,component,Canonical ontology/glossary signaling,opportunity-profile,component,Canonical ontology/glossary believed-action,opportunity-profile,component,Canonical ontology/glossary action,state-transition,may produce,Canonical ontology/glossary state-transition,system-state,changes,Canonical ontology/glossary agent,interaction-participant,subtype of,Canonical ontology/glossary environment,coupling,mediates,Canonical ontology/glossary token-identity,interaction-episode,identifies,Canonical ontology/glossary type-identity,interaction-episode,classifies,Canonical ontology/glossary similarity-contract,interaction-similarity,specifies,Canonical ontology/glossary strategy-contract,strategy,specifies,Canonical ontology/glossary interaction-contract,interaction-episode,specifies,Canonical ontology/glossary measurement-contract,behavioral-evidence,governs,Canonical ontology/glossary projection,scoped-invariance,tested across,Canonical ontology/glossary equivalence,scoped-invariance,expresses,Canonical ontology/glossary computational-interaction-science,interaction,studies,Canonical ontology/glossary ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Graphs/Knowledge_Graph_Nodes.csv (110 lines, 18.8 KiB) ======================================================================== id,label,type,definition,status,observable,latent,measurement domain-commitments,Domain commitments,Concept,"A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization system-state,System state,Concept,"The physical, computational, social, or modeled condition of a declared system at a particular time.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization semantic-assignment,Semantic assignment,Concept,"A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization semantic-state,Semantic state,Concept,The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state.,Proposed,No - latent/inferred,Yes,Requires latent-variable model information,Information,Concept,"A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization representation,Representation,Concept,"A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice. A representation may preserve, transform, omit, or introduce structure.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization projection,Projection,Concept,"A declared transformation from a target description, system state, or semantic assignment into an accessible representational form. A projection contract specifies: - target and authority; - mapping or construction rule; - interpretation assumptions; - preserved properties; - transformed properties; - omitted properties; - introduced properties; - available operations; - observer assumptions; - intended use; - context and scope; - uncertainty, tolerance, and failure conditions.",Proposed analytical role,Conditional on observation model,No or not inherently,Measure only under declared operationalization scoped-invariance,Scoped invariance,Concept,"A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance. Invariance must be typed. Relevant types include: - ontological; - semantic; - informational; - structural; - topological; - computational; - inferential; - task; - behavioral; - interactional.",Proposed theory,Conditional on observation model,No or not inherently,Measure only under declared operationalization interpretation,Interpretation,Concept,"The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose.",Proposed,No - latent/inferred,Yes,Requires latent-variable model interaction-participant,Interaction participant,Concept,"Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction. A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization agent,Agent,Concept,"An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization.",Proposed subtype,Conditional on observation model,No or not inherently,Measure only under declared operationalization environment,Environment,Concept,"The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization affordance,Affordance,Concept,"An action-relevant relation between an agent’s effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist.",Established external construct,Conditional on observation model,No or not inherently,Measure only under declared operationalization opportunity,Opportunity,Concept,"A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions. Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty.",Proposed coordination framework,Conditional on observation model,No or not inherently,Measure only under declared operationalization opportunity-profile,Opportunity profile,Concept,"For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations: - domain-valid; - effectively capable; - permitted; - enabled; - reachable outcomes; - exposed; - signaled; - believed available; - expected consequences; - selected; - executed; - successful; - reversible or recoverable; - uncertainty and provenance. Selected, executed, and successful are trace predicates rather than availability sets.",Proposed,Conditional on observation model,No or not inherently,Operationalizable by contract capability,Capability,Concept,The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions.,Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization permission,Permission,Concept,"Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization enablement,Enablement,Concept,The condition in which an action’s current-state preconditions are satisfied.,Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization reachability,Reachability,Concept,The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon.,Proposed,Conditional on observation model,No or not inherently,Operationalizable by contract exposure,Exposure,Concept,Provision by the current projection of an executable access path to an operation.,Proposed,Conditional on observation model,No or not inherently,Operationalizable by contract signaling,Signaling,Concept,"Perceivable information indicating an operation, condition, consequence, state, or recovery path.",Proposed,Conditional on observation model,No or not inherently,Operationalizable by contract discoverability,Discoverability,Concept,"The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions.",Proposed,Conditional on observation model,No or not inherently,Operationalizable by contract believed-action,Believed action,Concept,"An action represented by an agent as available, with an associated confidence and expected consequence.",Proposed latent variable,No - latent/inferred,Yes,Requires latent-variable model action,Action,Concept,"A declared intervention, command, operation, or behavior capable of participating in a state transition.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization state-transition,State transition,Concept,"A change from one declared system state to another under a transition relation, process, or event.",Proposed,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization observation,Observation,Concept,"A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process.",Proposed,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization situated-behavior,Situated behavior,Concept,"A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization behavioral-evidence,Behavioral evidence,Concept,"A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim.",Candidate,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization behavioral-equivalence,Behavioral equivalence,Concept,"Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance.",Candidate,Conditional on observation model,No or not inherently,Measure only under declared operationalization interactional-equivalence,Interactional equivalence,Concept,"Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions.",Candidate,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction,Interaction,Concept,"A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence.",Proposed scientific target,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction-episode,Interaction episode,Concept,"A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale. Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated.",Proposed canonical unit,Conditional on observation model,No or not inherently,Operationalizable by contract coupling,Coupling,Concept,"A relation or pathway through which a participant or shared medium can alter another participant's transition structure, reachable states, probabilities, timing, or constraints.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization perturbation,Perturbation,Concept,"A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization uptake,Uptake,Concept,"Incorporation of a perturbation into a participant's state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization recurrence,Recurrence,Concept,"Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction-contract,Interaction contract,Concept,"A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions.",Proposed reusable artifact,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction-morphology,Interaction morphology,Concept,"The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality.",Candidate,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction-grammar,Interaction grammar,Concept,A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation.,Candidate,Conditional on observation model,No or not inherently,Measure only under declared operationalization interaction-history,Interaction history,Concept,"The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent’s later beliefs, policies, and interpretation.",Candidate,Conditional on observation model,No or not inherently,Measure only under declared operationalization trace,Trace,Concept,"A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules.",Proposed,Directly/Instrumentally,No or not inherently,Operationalizable by contract measurement-contract,Measurement contract,Concept,"A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation.",Proposed reusable artifact,Conditional on observation model,No or not inherently,Operationalizable by contract interaction-similarity,Interaction similarity,Concept,"A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain.",Proposed typed comparison framework,Conditional on observation model,No or not inherently,Operationalizable by contract token-identity,Token identity,Concept,"Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization type-identity,Type identity,Concept,Membership in the same abstraction-defined interaction class under explicit classification rules.,Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization equivalence,Equivalence,Concept,Exact preservation under a declared comparison contract and observable set. Equivalence is always typed.,Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization similarity,Similarity,Concept,"Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization incomparability,Incomparability,Concept,"Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions.",Proposed,Conditional on observation model,No or not inherently,Measure only under declared operationalization similarity-contract,Similarity contract,Concept,"A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile.",Proposed reusable artifact,Conditional on observation model,No or not inherently,Measure only under declared operationalization strategy,Strategy,Concept,"An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states.",Proposed latent explanatory construct,No - latent/inferred,Yes,Requires latent-variable model strategy-contract,Strategy contract,Concept,"A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain.",Proposed reusable artifact,Conditional on observation model,No or not inherently,Measure only under declared operationalization policy,Policy,Concept,"A conditional relation from represented states, observations, or beliefs to action distributions.",Proposed,No - latent/inferred,Yes,Requires latent-variable model fundamental,Fundamental,Concept,"A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected.",Proposed research substrate,Conditional on observation model,No or not inherently,Measure only under declared operationalization computational-interaction-science,Foundations of Computational Interaction,Concept,"A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence. CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines.",Proposed research program; disciplinary autonomy unproven,Conditional on observation model,No or not inherently,Measure only under declared operationalization ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Artifact_Index.csv (68 lines, 13.6 KiB) ======================================================================== Path,Top-level category,Extension,Size bytes,SHA-256,Authority role 00_Project/CHANGELOG.md,00_Project,.md,511,0208a046f6936f8fff8cb52d192a726f533e59bc6f010f8815cc21e868ee4da8,External evidence 00_Project/README.md,00_Project,.md,1047,027b36f066ceb6dfb81e34ba5fd9dc26e9086a8ed0e3c7833319ee9a0587a227,External evidence 00_Project/VERSION,00_Project,,6,59854984853104df5c353e2f681a15fc7924742f9a2e468c29af248dce45ce03,External evidence 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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Definition_Index.csv (110 lines, 20.6 KiB) ======================================================================== Canonical ID,Term,Definition,Boundary,Authority,Status domain-commitments,Domain commitments,"A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology.","Domain commitments specify what the model admits. They do not by themselves assign meaning, produce a representation, or determine interpretation.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed system-state,System state,"The physical, computational, social, or modeled condition of a declared system at a particular time.","State is not synonymous with data, meaning, representation, or observation. A state becomes content-bearing only under a specified semantics.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed semantic-assignment,Semantic assignment,"A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain.",Formal semantic assignment is distinct from a person’s interpretation or understanding.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed semantic-state,Semantic state,The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state.,No observer-independent semantic state is assumed without an explicit theory and scope.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed information,Information,"A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use.","Information is not a synonym for stored variables, data, meaning, semantic state, or interpretation. Every claim that information is preserved must name the information theory, source, code, task, or relevance criterion.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed representation,Representation,"A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice. A representation may preserve, transform, omit, or introduce structure.","A representation is not identical with its target. Equal reference does not imply semantic, inferential, behavioral, or interactional equivalence.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed projection,Projection,"A declared transformation from a target description, system state, or semantic assignment into an accessible representational form. A projection contract specifies: - target and authority; - mapping or construction rule; - interpretation assumptions; - preserved properties; - transformed properties; - omitted properties; - introduced properties; - available operations; - observer assumptions; - intended use; - context and scope; - uncertainty, tolerance, and failure conditions.","Projection coordinates established concepts such as views, abstractions, encodings, lenses, simulations, model morphisms, and renderings. It is not a new metaphysical substance.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed analytical role scoped-invariance,Scoped invariance,"A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance. Invariance must be typed. Relevant types include: - ontological; - semantic; - informational; - structural; - topological; - computational; - inferential; - task; - behavioral; - interactional.",No one invariance type implies another.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed theory interpretation,Interpretation,"The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose.",Interpretation is a process or event. Semantics specifies or stabilizes admissible relations; interpretation applies or revises them.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed interaction-participant,Interaction participant,"Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction. A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning.","Interaction participant is the top-level role. More specific terms such as human participant, computational participant, institution, observer, mediator, autonomous agent, and AI agent should be used when their additional commitments matter.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed agent,Agent,"An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization.","Agent is not the universal term for every participant. An AI model is not automatically an agent; it becomes part of an agentic system when observations, action-selection, and consequential operations are supplied.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed subtype environment,Environment,"The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur.",The environment is not identical with what an agent can observe through a representation.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed affordance,Affordance,"An action-relevant relation between an agent’s effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist.","Affordance is not synonymous with permission, signaling, belief, execution success, or reversibility.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Established external construct opportunity,Opportunity,"A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions. Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed coordination framework opportunity-profile,Opportunity profile,"For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations: - domain-valid; - effectively capable; - permitted; - enabled; - reachable outcomes; - exposed; - signaled; - believed available; - expected consequences; - selected; - executed; - successful; - reversible or recoverable; - uncertainty and provenance. Selected, executed, and successful are trace predicates rather than availability sets.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed capability,Capability,The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions.,Capability is distinct from permission. Security capability tokens must be named explicitly when that narrower meaning is intended.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed permission,Permission,"Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation.",A prohibited action may remain technically possible.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed enablement,Enablement,The condition in which an action’s current-state preconditions are satisfied.,Enablement is local to the current state and differs from multi-step reachability.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed reachability,Reachability,The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon.,,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed exposure,Exposure,Provision by the current projection of an executable access path to an operation.,"An exposed operation may be hidden, poorly signaled, unknown, or inaccessible to a particular observer.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed signaling,Signaling,"Perceivable information indicating an operation, condition, consequence, state, or recovery path.","A signal may be true, incomplete, ambiguous, or false.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed discoverability,Discoverability,"The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions.",Discoverability is not a static visual property.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed believed-action,Believed action,"An action represented by an agent as available, with an associated confidence and expected consequence.",Belief cannot be read directly from non-selection or task completion. It requires elicitation or a validated inferential model.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed latent variable action,Action,"A declared intervention, command, operation, or behavior capable of participating in a state transition.",A low-level input such as a click or touch is not necessarily the semantic action under study.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed state-transition,State transition,"A change from one declared system state to another under a transition relation, process, or event.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed observation,Observation,"A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process.","Observation is not interpretation, inference, or evidence by itself.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed situated-behavior,Situated behavior,"A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model.",Representation does not determine behavior directly.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed behavioral-evidence,Behavioral evidence,"A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim.","A trace is evidence of what occurred. It is not direct evidence of intention, understanding, culture, personality, or protected identity.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate behavioral-equivalence,Behavioral equivalence,"Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance.","Behavioral equivalence does not imply semantic, interpretive, strategy, learning, transfer, or interactional equivalence.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate interactional-equivalence,Interactional equivalence,"Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate interaction,Interaction,"A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence.","Interaction is not reducible to action, behavior, communication, computation, observation, state transition, feedback, or causation alone. Ordinary-language usage may be broader than the strict research definition.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed scientific target interaction-episode,Interaction episode,"A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale. Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated.",A single isolated one-way causal effect is not an interaction episode under the strict definition unless it enters a recurrent or reciprocally constraining structure.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed canonical unit coupling,Coupling,"A relation or pathway through which a participant or shared medium can alter another participant's transition structure, reachable states, probabilities, timing, or constraints.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed perturbation,Perturbation,"A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed uptake,Uptake,"Incorporation of a perturbation into a participant's state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed recurrence,Recurrence,"Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed interaction-contract,Interaction contract,"A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed reusable artifact interaction-morphology,Interaction morphology,"The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality.",Morphology is not independent of all semantics or interpretation. A study must declare which content and operations are controlled.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate interaction-grammar,Interaction grammar,A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation.,,Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate interaction-history,Interaction history,"The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent’s later beliefs, policies, and interpretation.",Interaction history biases later behavior but does not fully explain or determine an individual.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Candidate trace,Trace,"A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules.","A trace is not identical with behavior, action, policy, strategy, intention, or mechanism.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed measurement-contract,Measurement contract,"A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation.",A metric is not a construct. Numerical output does not justify a latent interpretation without a validated measurement relation.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed reusable artifact interaction-similarity,Interaction similarity,"A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain.",There is no context-free universal similarity score.,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed typed comparison framework token-identity,Token identity,"Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed type-identity,Type identity,Membership in the same abstraction-defined interaction class under explicit classification rules.,,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed equivalence,Equivalence,Exact preservation under a declared comparison contract and observable set. Equivalence is always typed.,,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed similarity,Similarity,"Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed incomparability,Incomparability,"Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed similarity-contract,Similarity contract,"A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed reusable artifact strategy,Strategy,"An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states.","A strategy is not a single action, raw trace, repeated sequence, explicit plan, policy alone, skill, habit, or intention. It must be supported through rival discrimination, diagnostic contingencies, uncertainty, and evidence appropriate to the claim.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed latent explanatory construct strategy-contract,Strategy contract,"A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed reusable artifact policy,Policy,"A conditional relation from represented states, observations, or beliefs to action distributions.","A policy may be one component of a strategy. Strategy may additionally include information acquisition, commitment, resource allocation, switching, recovery, and stopping rules.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed fundamental,Fundamental,"A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected.","Fundamental is not the scientific theory, a philosophical ontology, proof of CIS, or a guarantee of shared human meaning.",Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed research substrate computational-interaction-science,Foundations of Computational Interaction,"A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence. CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines.",,Canonical Glossary v0.4 reconciled with Ontology v0.3,Proposed research program; disciplinary autonomy unproven ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Definition_Index.md (490 lines, 45.9 KiB) ======================================================================== **Canonical Definition Index** Version 1.0.0-integration.1 54 canonical records. The CSV/XLSX versions are the machine-readable systems of record. ---------------------------------------------------------------------------------------------------------------------- Canonical ID Term Definition Authority Status ----------------------------------- ----------------- ---------------------------------- -------------- -------------- domain-commitments Domain A set of commitments about Canonical Proposed commitments admissible entities, categories, Glossary v0.4 relations, identity conditions, reconciled modalities, and constraints in a with Ontology domain. In computational work, v0.3 these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology. system-state System state The physical, computational, Canonical Proposed social, or modeled condition of a Glossary v0.4 declared system at a particular reconciled time. with Ontology v0.3 semantic-assignment Semantic A rule-governed assignment of Canonical Proposed assignment content, denotation, truth Glossary v0.4 conditions, inferential reconciled consequences, or transition with Ontology behavior to expressions, states, v0.3 signs, or operations within a specified system and domain. semantic-state Semantic state The content-bearing assignments Canonical Proposed and relations currently licensed Glossary v0.4 by a specified semantics for a reconciled system or discourse state. with Ontology v0.3 information Information A typed measure or Canonical Proposed characterization of distinctions, Glossary v0.4 correlations, descriptions, or reconciled content relative to a specified with Ontology source, code, semantic relation, v0.3 probability model, or use. representation Representation A materially or formally realized Canonical Proposed vehicle that provides selective Glossary v0.4 access to a declared target reconciled through a mapping or with Ontology correspondence and an interpretive v0.3 practice.\ \ A representation may preserve, transform, omit, or introduce structure. projection Projection A declared transformation from a Canonical Proposed target description, system state, Glossary v0.4 analytical or semantic assignment into an reconciled role accessible representational form.\ with Ontology \ v0.3 A projection contract specifies:\ \ - target and authority;\ - mapping or construction rule;\ - interpretation assumptions;\ - preserved properties;\ - transformed properties;\ - omitted properties;\ - introduced properties;\ - available operations;\ - observer assumptions;\ - intended use;\ - context and scope;\ - uncertainty, tolerance, and failure conditions. scoped-invariance Scoped invariance A declared property remains Canonical Proposed invariant across projections when Glossary v0.4 theory independently specified comparison reconciled rules show that it is preserved with Ontology for a stated target, observer v0.3 class, context, metric, and tolerance.\ \ Invariance must be typed. Relevant types include:\ \ - ontological;\ - semantic;\ - informational;\ - structural;\ - topological;\ - computational;\ - inferential;\ - task;\ - behavioral;\ - interactional. interpretation Interpretation The application, recovery, Canonical Proposed construction, negotiation, or Glossary v0.4 revision of semantic relations by reconciled an interpreting system under a with Ontology context, competence, history, and v0.3 purpose. interaction-participant Interaction Any bounded person, collective, Canonical Proposed participant organism, computational process, Glossary v0.4 artificial system, institution, or reconciled hybrid arrangement occupying a with Ontology consequential role within an v0.3 interaction.\ \ A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning. agent Agent An acting interaction participant Canonical Proposed that selects or produces actions Glossary v0.4 subtype through a policy, rule, control reconciled process, intention, or other with Ontology action-selection organization. v0.3 environment Environment The declared physical, Canonical Proposed computational, social, symbolic, Glossary v0.4 or mixed system within which reconciled action and state transition occur. with Ontology v0.3 affordance Affordance An action-relevant relation Canonical Established between an agent's effectivities Glossary v0.4 external or capabilities and environmental reconciled construct structure that makes a class of with Ontology action possible. In the Gibsonian v0.3 sense, perception is not required for the affordance to exist. opportunity Opportunity A typed and indexed analytical Canonical Proposed profile coordinating Glossary v0.4 coordination action-availability relations reconciled framework under declared system, agent, with Ontology projection, task, authority, v0.3 state, and temporal conditions.\ \ Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty. opportunity-profile Opportunity For an agent, action, state, Canonical Proposed profile projection, and time, an Glossary v0.4 opportunity profile records the reconciled relevant typed relations:\ with Ontology \ v0.3 - domain-valid;\ - effectively capable;\ - permitted;\ - enabled;\ - reachable outcomes;\ - exposed;\ - signaled;\ - believed available;\ - expected consequences;\ - selected;\ - executed;\ - successful;\ - reversible or recoverable;\ - uncertainty and provenance.\ \ Selected, executed, and successful are trace predicates rather than availability sets. capability Capability The effective capacity or Canonical Proposed resources required for an Glossary v0.4 agent-system coupling to execute reconciled an action or bring about an with Ontology outcome under declared conditions. v0.3 permission Permission Authorization under a policy, Canonical Proposed role, rule, authority, or Glossary v0.4 institutional condition for a reconciled subject to perform an operation. with Ontology v0.3 enablement Enablement The condition in which an action's Canonical Proposed current-state preconditions are Glossary v0.4 satisfied. reconciled with Ontology v0.3 reachability Reachability The existence of at least one Canonical Proposed admissible transition sequence Glossary v0.4 from a declared initial state to a reconciled target state or outcome within with Ontology specified constraints and horizon. v0.3 exposure Exposure Provision by the current Canonical Proposed projection of an executable access Glossary v0.4 path to an operation. reconciled with Ontology v0.3 signaling Signaling Perceivable information indicating Canonical Proposed an operation, condition, Glossary v0.4 consequence, state, or recovery reconciled path. with Ontology v0.3 discoverability Discoverability The empirically observed Canonical Proposed probability and process by which Glossary v0.4 an agent identifies an action or reconciled relation under declared task, with Ontology projection, knowledge, modality, v0.3 context, and time conditions. believed-action Believed action An action represented by an agent Canonical Proposed as available, with an associated Glossary v0.4 latent confidence and expected reconciled variable consequence. with Ontology v0.3 action Action A declared intervention, command, Canonical Proposed operation, or behavior capable of Glossary v0.4 participating in a state reconciled transition. with Ontology v0.3 state-transition State transition A change from one declared system Canonical Proposed state to another under a Glossary v0.4 transition relation, process, or reconciled event. with Ontology v0.3 observation Observation A recorded or accessible Canonical Proposed distinction about state, Glossary v0.4 transition, representation, or reconciled outcome available through a with Ontology specified measurement or v0.3 observation process. situated-behavior Situated behavior A bounded, temporally extended Canonical Proposed trajectory of observable or Glossary v0.4 instrumentally recoverable reconciled changes, outputs, or regulated with Ontology persistence attributed to a system v0.3 in relation to its environment under a declared observation and attribution model. behavioral-evidence Behavioral A provenance-preserving chain Canonical Candidate evidence connecting direct observations, Glossary v0.4 system-derived features, latent reconciled interpretations, alternative with Ontology explanations, uncertainty, and v0.3 falsifying evidence to a bounded research claim. behavioral-equivalence Behavioral Equivalence of declared action or Canonical Candidate equivalence outcome distributions for a Glossary v0.4 specified population, task, reconciled context, metric, and tolerance. with Ontology v0.3 interactional-equivalence Interactional Equivalence of the available Canonical Candidate equivalence operation-transition-observation Glossary v0.4 structure under specified agent, reconciled task, projection, authority, with Ontology state, context, and tolerance v0.3 conditions. interaction Interaction A family of bounded coupling Canonical Proposed phenomena in which distinguishable Glossary v0.4 scientific systems or participants become reconciled target mutually consequential through with Ontology perturbation, constraint, uptake, v0.3 response, and recurrence. interaction-episode Interaction A bounded interval in which two or Canonical Proposed episode more distinguishable systems are Glossary v0.4 canonical unit coupled such that perturbations reconciled originating in, or mediated by, with Ontology one system alter the possible or v0.3 actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale.\ \ Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated. coupling Coupling A relation or pathway through Canonical Proposed which a participant or shared Glossary v0.4 medium can alter another reconciled participant\'s transition with Ontology structure, reachable states, v0.3 probabilities, timing, or constraints. perturbation Perturbation A difference propagated through a Canonical Proposed coupling relation that may change Glossary v0.4 state, transition conditions, reconciled probabilities, timing, or with Ontology reachable outcomes. v0.3 uptake Uptake Incorporation of a perturbation Canonical Proposed into a participant\'s state, Glossary v0.4 transition process, control reconciled process, or interpreted situation. with Ontology Uptake need not be semantic or v0.3 conscious. recurrence Recurrence Return influence through which a Canonical Proposed response constrains an originating Glossary v0.4 participant, a co-participant, or reconciled the shared coupling configuration. with Ontology v0.3 interaction-contract Interaction A declaration of interaction Canonical Proposed contract identity, participants and roles, Glossary v0.4 reusable boundary, timescale, state, reconciled artifact coupling, preconditions, events, with Ontology transitions, protocol, invariants, v0.3 evidence, failure, recovery, and completion conditions. interaction-morphology Interaction The measurable structural Canonical Candidate morphology properties of a representation or Glossary v0.4 interaction surface, such as reconciled hierarchy, topology, density, with Ontology alignment, rhythm, symmetry, v0.3 enclosure, continuity, direction, visual weight, temporal organization, and modality. interaction-grammar Interaction A typed vocabulary and composition Canonical Candidate grammar structure for semantic actions and Glossary v0.4 transitions independent of any one reconciled input modality or rendering with Ontology implementation. v0.3 interaction-history Interaction The accumulated experience, Canonical Candidate history training, conventions, outcomes, Glossary v0.4 failures, practices, and prior reconciled exposure that may change an with Ontology agent's later beliefs, policies, v0.3 and interpretation. trace Trace A temporally ordered or partially Canonical Proposed ordered record of observable or Glossary v0.4 attributed events under declared reconciled boundaries, granularity, and with Ontology observation rules. v0.3 measurement-contract Measurement A declaration of the measurand, Canonical Proposed contract observation process, Glossary v0.4 reusable operationalization, scale, reconciled artifact uncertainty, validity evidence, with Ontology population, task, projection, v0.3 comparison conditions, and permitted interpretation. interaction-similarity Interaction A comparison of interaction Canonical Proposed typed similarity tokens, types, structures, Glossary v0.4 comparison protocols, opportunities, traces, reconciled framework behaviors, policies, strategies, with Ontology outcomes, causes, or measurements v0.3 under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain. token-identity Token identity Historical identity of one bounded Canonical Proposed interaction episode under declared Glossary v0.4 continuity, participant, boundary, reconciled and timescale criteria. with Ontology v0.3 type-identity Type identity Membership in the same Canonical Proposed abstraction-defined interaction Glossary v0.4 class under explicit reconciled classification rules. with Ontology v0.3 equivalence Equivalence Exact preservation under a Canonical Proposed declared comparison contract and Glossary v0.4 observable set. Equivalence is reconciled always typed. with Ontology v0.3 similarity Similarity Graded proximity under declared Canonical Proposed dimensions, representations, Glossary v0.4 alignment rules, metrics, weights, reconciled tolerances, and uncertainty. with Ontology v0.3 incomparability Incomparability Failure to establish a defensible Canonical Proposed common comparison space because Glossary v0.4 boundaries, targets, mappings, reconciled scales, observation processes, with Ontology uncertainty, or validity domains v0.3 cannot be aligned without unsupported assumptions. similarity-contract Similarity A declaration of comparison Canonical Proposed contract target, frame, representations, Glossary v0.4 reusable correspondence mapping, reconciled artifact invariants, variants, observables, with Ontology admissible and prohibited v0.3 transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile. strategy Strategy An inferred, temporally extended Canonical Proposed organization of conditional action Glossary v0.4 latent selection, information use, reconciled explanatory resource allocation, and with Ontology construct contingency response that tends to v0.3 preserve or improve one or more criteria across a declared class of interaction states. strategy-contract Strategy contract A declaration of strategy-bearing Canonical Proposed system, domain, timescale, Glossary v0.4 reusable criteria, state and observation reconciled artifact model, state abstraction, with Ontology opportunity assumptions, action v0.3 repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain. policy Policy A conditional relation from Canonical Proposed represented states, observations, Glossary v0.4 or beliefs to action reconciled distributions. with Ontology v0.3 fundamental Fundamental A representation-independent Canonical Proposed computational substrate for Glossary v0.4 research declaring domain commitments, reconciled substrate evolving system state, assigning with Ontology operational semantics, and v0.3 producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected. computational-interaction-science Computational A research program that studies Canonical Proposed Interaction interaction as an explanatory Glossary v0.4 research Science target by separating and comparing reconciled program; declared domain commitments, with Ontology disciplinary state, semantics, projection, v0.3 autonomy representation, interpretation, unproven opportunity, coupling, behavior, measurement, similarity, strategy, and evidence.\ \ CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer scien ---------------------------------------------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Figure_Index.csv (19 lines, 3.6 KiB) ======================================================================== Paper ID,Paper,Figure/Caption,Embedded Media Count,Table Count,Source DOCX 01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM","Figure 1. Dependency graph for the minimum ontology. Arrows indicate explanatory dependence, not necessarily temporal precedence.",1,8,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx 02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",Table 1 compares scientific structure rather than disciplinary history. “Observer” identifies the investigator or measurement system; “observed” identifies the focal target. The rows are ideal types: each discipline contains internal disagreement and subfields that cross the stated boundary.,0,5,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx 03,How Sciences Define Their Objects,"Table 1 records dominant structures rather than exhaustive internal diversity. 'Observer' identifies the epistemic role that selects and records evidence, not necessarily a person external to the system. 'Mechanism/dependency' includes lawful, causal, structural, functional, historical, computational, interpretive, and statistical forms.",0,6,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx 04,"Representation, Invariance, and Projection",No explicit caption detected,0,6,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx 05,"Ontology, Semantics, Representation, and Interpretation","Table 7 is the reusable transformation matrix. Its rule is that invariance must be typed and tested independently for ontology, formal semantics, information, representation, interpretation, and behavior.",0,9,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx 06,"Opportunity, Affordance, and Action Availability",No explicit caption detected,0,3,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx 07,Interaction,No explicit caption detected,0,3,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx 08,Behavior,No explicit caption detected,0,8,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx 09,Measurement,No explicit caption detected,0,4,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx 10,Interaction Similarity,No explicit caption detected,0,5,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx 11,Interaction Transfer,No explicit caption detected,0,3,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx 12,Interaction Strategies,No explicit caption detected,0,3,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx 13,Formal Models of Computational Interaction,No explicit caption detected,0,3,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx 14,Predicting Interaction,No explicit caption detected,0,9,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx 15,Comparative Interaction,No explicit caption detected,0,8,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx 16,Foundations of Computational Interaction,No explicit caption detected,0,7,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Figure_Index.md (95 lines, 8.2 KiB) ======================================================================== **Canonical Figure Index** Version 1.0.0-integration.1 16 indexed records. The CSV/XLSX file is authoritative for machine processing. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Paper ID Paper Figure/Caption Embedded Table Count Source DOCX Media Count ----------- ----------------- -------------------------- ----------- ----------- ------------------------------------------------------------------------------------------------------------------------------------------------ 01 INTERACTION AS A\ Figure 1. Dependency graph 1 8 02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx SCIENTIFIC for the minimum ontology. EXPLANANDUM Arrows indicate explanatory dependence, not necessarily temporal precedence. 02 CAN INTERACTION Table 1 compares 0 5 02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx BECOME A\ scientific structure PRIMARY rather than disciplinary SCIENTIFIC history. "Observer" OBJECT? identifies the investigator or measurement system; "observed" identifies the focal target. The rows are ideal types: each discipline contains internal disagreement and 03 How Sciences Table 1 records dominant 0 6 02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx Define Their structures rather than Objects exhaustive internal diversity. \'Observer\' identifies the epistemic role that selects and records evidence, not necessarily a person external to the system. \'Mechanism/dependency\' includes lawful, causal 04 Representation, No explicit caption 0 6 02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx Invariance, and detected Projection 05 Ontology, Table 7 is the reusable 0 9 02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx Semantics, transformation matrix. Its Representation, rule is that invariance and must be typed and tested Interpretation independently for ontology, formal semantics, information, representation, interpretation, and behavior. 06 Opportunity, No explicit caption 0 3 02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx Affordance, and detected Action Availability 07 Interaction No explicit caption 0 3 02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx detected 08 Behavior No explicit caption 0 8 02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx detected 09 Measurement No explicit caption 0 4 02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx detected 10 Interaction No explicit caption 0 5 02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx Similarity detected 11 Interaction No explicit caption 0 3 02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx Transfer detected 12 Interaction No explicit caption 0 3 02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx Strategies detected 13 Formal Models of No explicit caption 0 3 02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx Computational detected Interaction 14 Predicting No explicit caption 0 9 02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx Interaction detected 15 Comparative No explicit caption 0 8 02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx Interaction detected 16 Computational No explicit caption 0 7 02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx Interaction detected Science --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Vocabulary.csv (147 lines, 37.3 KiB) ======================================================================== canonical_id,term,maturity,definition,boundary,aliases,deprecated_terminology,dependencies,observable_status,latent_status,measurement_status,originating_paper,supporting_papers,supporting_literature,contracts,formal_mappings,example,counterexample domain-commitments,Domain commitments,Proposed,"A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology.","Domain commitments specify what the model admits. They do not by themselves assign meaning, produce a representation, or determine interpretation.",ontology commitments,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Ontology, Semantics, Representation, and Interpretation","Ontology, Semantics, Representation, and Interpretation; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",,,,, system-state,System state,Proposed,"The physical, computational, social, or modeled condition of a declared system at a particular time.","State is not synonymous with data, meaning, representation, or observation. A state becomes content-bearing only under a specified semantics.",state,,Domain commitments; State transition,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Ontology, Semantics, Representation, and Interpretation; Interaction; Interaction Strategies; Predicting Interaction",,Projection Contract; Opportunity Contract; Interaction Contract; Behavioral Evidence Contract; Measurement Contract; Similarity Contract; Transfer Contract; Strategy Contract; Prediction Contract,Layered observation-enriched probabilistic labeled transition system,, semantic-assignment,Semantic assignment,Proposed,"A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain.",Formal semantic assignment is distinct from a person’s interpretation or understanding.,formal semantics,,Domain commitments,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Ontology, Semantics, Representation, and Interpretation","Ontology, Semantics, Representation, and Interpretation",,,,, semantic-state,Semantic state,Proposed,The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state.,No observer-independent semantic state is assumed without an explicit theory and scope.,,,Semantic assignment,No - latent/inferred,Yes,Requires latent-variable model,"Ontology, Semantics, Representation, and Interpretation","Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; Foundations of Computational Interaction",,,,, information,Information,Proposed,"A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use.","Information is not a synonym for stored variables, data, meaning, semantic state, or interpretation. Every claim that information is preserved must name the information theory, source, code, task, or relevance criterion.",,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Ontology, Semantics, Representation, and Interpretation","Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; Interaction Strategies; Predicting Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM",,,,, representation,Representation,Proposed,"A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice. A representation may preserve, transform, omit, or introduce structure.","A representation is not identical with its target. Equal reference does not imply semantic, inferential, behavioral, or interactional equivalence.",representational vehicle,,Projection,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Representation, Invariance, and Projection","Representation, Invariance, and Projection; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Ontology, Semantics, Representation, and Interpretation; Interaction Transfer; Foundations of Computational Interaction",,,,A table and graph that selectively expose the same declared target.,"The target itself, treated as identical with its representation." projection,Projection,Proposed analytical role,"A declared transformation from a target description, system state, or semantic assignment into an accessible representational form. A projection contract specifies: - target and authority; - mapping or construction rule; - interpretation assumptions; - preserved properties; - transformed properties; - omitted properties; - introduced properties; - available operations; - observer assumptions; - intended use; - context and scope; - uncertainty, tolerance, and failure conditions.","Projection coordinates established concepts such as views, abstractions, encodings, lenses, simulations, model morphisms, and renderings. It is not a new metaphysical substance.",view; encoding; rendering,,System state; Semantic assignment,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Representation, Invariance, and Projection; Formal Models of Computational Interaction; Foundations of Computational Interaction; Predicting Interaction",,Projection Contract,,"A declared mapping from a system state to a GUI, API, or auditory form.","An implementation artifact with no declared target, mapping, or scope." scoped-invariance,Scoped invariance,Proposed theory,"A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance. Invariance must be typed. Relevant types include: - ontological; - semantic; - informational; - structural; - topological; - computational; - inferential; - task; - behavioral; - interactional.",No one invariance type implies another.,,semantic invariance,Projection; Equivalence,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Canonical glossary,,,,,, interpretation,Interpretation,Proposed,"The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose.",Interpretation is a process or event. Semantics specifies or stabilizes admissible relations; interpretation applies or revises them.,,,Representation; Interaction history,No - latent/inferred,Yes,Requires latent-variable model,"Ontology, Semantics, Representation, and Interpretation","Ontology, Semantics, Representation, and Interpretation; Representation, Invariance, and Projection; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Measurement; Foundations of Computational Interaction",,,,An agent applies conventions and context to a signaled operation.,Formal semantics treated as identical to a participant’s understanding. interaction-participant,Interaction participant,Proposed,"Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction. A participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. Participation does not imply autonomy, intelligence, consciousness, or learning.","Interaction participant is the top-level role. More specific terms such as human participant, computational participant, institution, observer, mediator, autonomous agent, and AI agent should be used when their additional commitments matter.",participant,,Agent,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Canonical glossary,,,Interaction Contract,Layered observation-enriched probabilistic labeled transition system,, agent,Agent,Proposed subtype,"An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization.","Agent is not the universal term for every participant. An AI model is not automatically an agent; it becomes part of an agentic system when observations, action-selection, and consequential operations are supplied.",,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Interaction; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Formal Models of Computational Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM",,,,, environment,Environment,Proposed,"The declared physical, computational, social, symbolic, or mixed system within which action and state transition occur.",The environment is not identical with what an agent can observe through a representation.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Behavior,"Behavior; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Ontology, Semantics, Representation, and Interpretation",,,,, affordance,Affordance,Established external construct,"An action-relevant relation between an agent’s effectivities or capabilities and environmental structure that makes a class of action possible. In the Gibsonian sense, perception is not required for the affordance to exist.","Affordance is not synonymous with permission, signaling, belief, execution success, or reversibility.",,perceived affordance,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Representation, Invariance, and Projection; Ontology, Semantics, Representation, and Interpretation; Predicting Interaction",,,,, opportunity,Opportunity,Proposed coordination framework,"A typed and indexed analytical profile coordinating action-availability relations under declared system, agent, projection, task, authority, state, and temporal conditions. Opportunity is not a new primitive. It coordinates established relations such as feasibility, capability, permission, enablement, reachability, exposure, signaling, belief, expected consequence, reversibility, and uncertainty.",,,opportunity as a primitive,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Interaction Similarity; Interaction Strategies; Foundations of Computational Interaction; Predicting Interaction",,Opportunity Contract,,, opportunity-profile,Opportunity profile,Proposed,"For an agent, action, state, projection, and time, an opportunity profile records the relevant typed relations: - domain-valid; - effectively capable; - permitted; - enabled; - reachable outcomes; - exposed; - signaled; - believed available; - expected consequences; - selected; - executed; - successful; - reversible or recoverable; - uncertainty and provenance. Selected, executed, and successful are trace predicates rather than availability sets.",,typed opportunity profile,opportunity as a primitive,Interpretation; System state; Projection; Affordance; Capability; Permission; Enablement; Reachability; Exposure; Signaling; Believed action,Conditional on observation model,No or not inherently,Operationalizable by contract,"Representation, Invariance, and Projection","Representation, Invariance, and Projection; Opportunity, Affordance, and Action Availability; Behavior; Interaction Similarity; Interaction Strategies",,Opportunity Contract,Layered observation-enriched probabilistic labeled transition system,"A profile distinguishing permitted, enabled, exposed, signaled, and believed actions.",A visible control treated as proof that an action is feasible or believed. capability,Capability,Proposed,The effective capacity or resources required for an agent-system coupling to execute an action or bring about an outcome under declared conditions.,Capability is distinct from permission. Security capability tokens must be named explicitly when that narrower meaning is intended.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Foundations of Computational Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Interaction",,,,, permission,Permission,Proposed,"Authorization under a policy, role, rule, authority, or institutional condition for a subject to perform an operation.",A prohibited action may remain technically possible.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Foundations of Computational Interaction; Behavior; Interaction Similarity; Interaction Strategies",,,,, enablement,Enablement,Proposed,The condition in which an action’s current-state preconditions are satisfied.,Enablement is local to the current state and differs from multi-step reachability.,enabled action,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction",,,,, reachability,Reachability,Proposed,The existence of at least one admissible transition sequence from a declared initial state to a target state or outcome within specified constraints and horizon.,,,,,Conditional on observation model,No or not inherently,Operationalizable by contract,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction; Interaction",,,,, exposure,Exposure,Proposed,Provision by the current projection of an executable access path to an operation.,"An exposed operation may be hidden, poorly signaled, unknown, or inaccessible to a particular observer.",operation exposure,,,Conditional on observation model,No or not inherently,Operationalizable by contract,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Interaction Transfer; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Predicting Interaction; Formal Models of Computational Interaction",,,,, signaling,Signaling,Proposed,"Perceivable information indicating an operation, condition, consequence, state, or recovery path.","A signal may be true, incomplete, ambiguous, or false.",signifier,perceived affordance,,Conditional on observation model,No or not inherently,Operationalizable by contract,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Foundations of Computational Interaction; Formal Models of Computational Interaction; Predicting Interaction; Comparative Interaction",,,,, discoverability,Discoverability,Proposed,"The empirically observed probability and process by which an agent identifies an action or relation under declared task, projection, knowledge, modality, context, and time conditions.",Discoverability is not a static visual property.,,perceived affordance,,Conditional on observation model,No or not inherently,Operationalizable by contract,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; Measurement; Representation, Invariance, and Projection; Interaction Transfer; Comparative Interaction",,,,, believed-action,Believed action,Proposed latent variable,"An action represented by an agent as available, with an associated confidence and expected consequence.",Belief cannot be read directly from non-selection or task completion. It requires elicitation or a validated inferential model.,believed availability,perceived affordance,Interaction history,No - latent/inferred,Yes,Requires latent-variable model,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Interaction Similarity; Interaction Transfer; Predicting Interaction",,,,, action,Action,Proposed,"A declared intervention, command, operation, or behavior capable of participating in a state transition.",A low-level input such as a click or touch is not necessarily the semantic action under study.,,perceived affordance; interaction causes behavior,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Opportunity, Affordance, and Action Availability","Opportunity, Affordance, and Action Availability; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Interaction Strategies; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Behavior",,Interaction Contract,,, state-transition,State transition,Proposed,"A change from one declared system state to another under a transition relation, process, or event.",,transition,,Action,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization,Interaction,"Interaction; Behavior; INTERACTION AS A SCIENTIFIC EXPLANANDUM; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",,,,, observation,Observation,Proposed,"A recorded or accessible distinction about state, transition, representation, or outcome available through a specified measurement or observation process.","Observation is not interpretation, inference, or evidence by itself.",,,,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization,Formal Models of Computational Interaction,"Formal Models of Computational Interaction; Measurement; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Interaction Strategies; Interaction Similarity",,Projection Contract; Opportunity Contract; Interaction Contract; Behavioral Evidence Contract; Measurement Contract; Similarity Contract; Transfer Contract; Strategy Contract; Prediction Contract,,, situated-behavior,Situated behavior,Proposed,"A bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system in relation to its environment under a declared observation and attribution model.",Representation does not determine behavior directly.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Canonical glossary,,,,,, behavioral-evidence,Behavioral evidence,Candidate,"A provenance-preserving chain connecting direct observations, system-derived features, latent interpretations, alternative explanations, uncertainty, and falsifying evidence to a bounded research claim.","A trace is evidence of what occurred. It is not direct evidence of intention, understanding, culture, personality, or protected identity.",behavior evidence,,Measurement contract,Directly/Instrumentally,No or not inherently,Measure only under declared operationalization,Behavior,"Behavior; Foundations of Computational Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Formal Models of Computational Interaction; Comparative Interaction",,Behavioral Evidence Contract,,, behavioral-equivalence,Behavioral equivalence,Candidate,"Equivalence of declared action or outcome distributions for a specified population, task, context, metric, and tolerance.","Behavioral equivalence does not imply semantic, interpretive, strategy, learning, transfer, or interactional equivalence.",,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"Representation, Invariance, and Projection","Representation, Invariance, and Projection; Interaction Similarity; Formal Models of Computational Interaction; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability",,Behavioral Evidence Contract,,, interactional-equivalence,Interactional equivalence,Candidate,"Equivalence of the available operation-transition-observation structure under specified agent, task, projection, authority, state, context, and tolerance conditions.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"INTERACTION AS A SCIENTIFIC EXPLANANDUM","INTERACTION AS A SCIENTIFIC EXPLANANDUM; Representation, Invariance, and Projection; Interaction Similarity",,,,, interaction,Interaction,Proposed scientific target,"A family of bounded coupling phenomena in which distinguishable systems or participants become mutually consequential through perturbation, constraint, uptake, response, and recurrence.","Interaction is not reducible to action, behavior, communication, computation, observation, state transition, feedback, or causation alone. Ordinary-language usage may be broader than the strict research definition.",,interaction causes behavior,Foundations of Computational Interaction,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,"Interaction; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Foundations of Computational Interaction; Predicting Interaction","(1982) Human-computer interaction: a preliminary RUDD,J., STERN, K. R. AND ISENSEE, S. (1996) Low social psychological analysis. Behavior Research: vs. High-fidelity Prototyping Debate. ACM Inter- Methods and Instrumentation,13, (2), 210-220. actions Magazine, January, 76-85. References 501; (1993) Human-Computer Interaction (2nd ed.). Analysis: Verbal Reports as Data. Cambridge, MA: London: Prentice-Hall Europe. The MIT Press.; (1993) Project Ernestine: validating a GOMS J. (1993) Unpacking collaboration: the interac- analysis for predicting and explaining real-world tional organization of trading in a city dealing performance. Human-Computer Interaction, 8(3), room. In Proceedings of the Third European Con- 237-309. ference on Computer-Supported Cooperative; 1. Interview: reproduced by permission of IDEO. (1997) Tangible Bits: towards seamless interfaces, in CH1'97 Proceedings, reprinted by permission of Chapter 2 Association for Computing Machinery, Inc.; Figure Figure 2.1 (on Color Plate 2): gif from www.ai.mit. 2.1 1 (ii) gif from www.almaden.ibm.com/cs/blueeyes/ edu/projects/medical-visionlsurgeryl reproduced by permission of IBM; Figure 2.11 (iii): gif surgical-navigation.htm1 reproduced by permission from www.parc.xerox.com/red/members/richgold/ of Michael E. Leventon; Figure 2.6(a): gif from livingdoc/slide6. html, reproduced by permission of http://vibes.cs.uiuc.edu/ProjectNRIVirtuelVirtueOve Rich Gold of PARC Communications; Figure 2.12: rview.htm, reproduced by permission of Dr Daniel A. gif from www.mbay.net/-brendaWarticleslPDA. Reed (University of Illinois at Urbana-Champaign) Mar.951 reproduced by permission of General Magic, from work on the Collaborative Virtual Inc.",Interaction Contract,,, interaction-episode,Interaction episode,Proposed canonical unit,"A bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of another, and the resulting configuration constrains a later trajectory of an originating or co-participating system within a declared boundary and timescale. Reciprocal closure may be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated.",A single isolated one-way causal effect is not an interaction episode under the strict definition unless it enters a recurrent or reciprocally constraining structure.,strict interaction episode,,Opportunity profile; Coupling; Token identity; Type identity; Interaction contract,Conditional on observation model,No or not inherently,Operationalizable by contract,Interaction,"Interaction; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Formal Models of Computational Interaction; Foundations of Computational Interaction; Predicting Interaction",,Interaction Contract,Layered observation-enriched probabilistic labeled transition system,"A request, response, and later state-dependent continuation within a declared protocol boundary.",A one-way message with no reciprocal or recurrent constraint inside the declared episode. coupling,Coupling,Proposed,"A relation or pathway through which a participant or shared medium can alter another participant's transition structure, reachable states, probabilities, timing, or constraints.",,,,Interaction participant; Environment,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,"Interaction; CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Formal Models of Computational Interaction; How Sciences Define Their Objects",,,Layered observation-enriched probabilistic labeled transition system,, perturbation,Perturbation,Proposed,"A difference propagated through a coupling relation that may change state, transition conditions, probabilities, timing, or reachable outcomes.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,"Interaction; INTERACTION AS A SCIENTIFIC EXPLANANDUM",,,,, uptake,Uptake,Proposed,"Incorporation of a perturbation into a participant's state, transition process, control process, or interpreted situation. Uptake need not be semantic or conscious.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,"Interaction; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability",,,,, recurrence,Recurrence,Proposed,"Return influence through which a response constrains an originating participant, a co-participant, or the shared coupling configuration.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,Interaction; Interaction Strategies; Behavior,,,,, interaction-contract,Interaction contract,Proposed reusable artifact,"A declaration of interaction identity, participants and roles, boundary, timescale, state, coupling, preconditions, events, transitions, protocol, invariants, evidence, failure, recovery, and completion conditions.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,Interaction; Foundations of Computational Interaction; Comparative Interaction,,Interaction Contract,,, interaction-morphology,Interaction morphology,Candidate,"The measurable structural properties of a representation or interaction surface, such as hierarchy, topology, density, alignment, rhythm, symmetry, enclosure, continuity, direction, visual weight, temporal organization, and modality.",Morphology is not independent of all semantics or interpretation. A study must declare which content and operations are controlled.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Canonical glossary,,,Interaction Contract,,, interaction-grammar,Interaction grammar,Candidate,A typed vocabulary and composition structure for semantic actions and transitions independent of any one input modality or rendering implementation.,,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?","CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; Interaction",,Interaction Contract,,, interaction-history,Interaction history,Candidate,"The accumulated experience, training, conventions, outcomes, failures, practices, and prior exposure that may change an agent’s later beliefs, policies, and interpretation.",Interaction history biases later behavior but does not fully explain or determine an individual.,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"INTERACTION AS A SCIENTIFIC EXPLANANDUM","INTERACTION AS A SCIENTIFIC EXPLANANDUM",,Interaction Contract,,, trace,Trace,Proposed,"A temporally ordered or partially ordered record of observable or attributed events under declared boundaries, granularity, and observation rules.","A trace is not identical with behavior, action, policy, strategy, intention, or mechanism.",interaction trace; behavioral trace,,Observation,Directly/Instrumentally,No or not inherently,Operationalizable by contract,Interaction Similarity,Interaction Similarity; Behavior; Interaction Strategies; Interaction; Predicting Interaction,,Projection Contract; Opportunity Contract; Interaction Contract; Behavioral Evidence Contract; Measurement Contract; Similarity Contract; Transfer Contract; Strategy Contract; Prediction Contract,Layered observation-enriched probabilistic labeled transition system,, measurement-contract,Measurement contract,Proposed reusable artifact,"A declaration of the measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, comparison conditions, and permitted interpretation.",A metric is not a construct. Numerical output does not justify a latent interpretation without a validated measurement relation.,,,Trace,Conditional on observation model,No or not inherently,Operationalizable by contract,Measurement,Measurement; Formal Models of Computational Interaction; Foundations of Computational Interaction; Behavior; Interaction Transfer,,Measurement Contract,,"A declaration of measurand, observation process, scale, uncertainty, and admissible inference.",A response-time column treated as a construct without validity conditions. interaction-similarity,Interaction similarity,Proposed typed comparison framework,"A comparison of interaction tokens, types, structures, protocols, opportunities, traces, behaviors, policies, strategies, outcomes, causes, or measurements under an explicit frame, correspondence mapping, admissible transformations, metrics, tolerances, uncertainty, and validity domain.",There is no context-free universal similarity score.,,,Measurement contract; Similarity contract,Conditional on observation model,No or not inherently,Operationalizable by contract,"INTERACTION AS A SCIENTIFIC EXPLANANDUM","INTERACTION AS A SCIENTIFIC EXPLANANDUM; Interaction Similarity; Predicting Interaction; Comparative Interaction; Foundations of Computational Interaction",,Interaction Contract,,"A typed profile comparing protocol, opportunity, trace, and outcome dimensions.",One aggregate score presented without a comparison contract. token-identity,Token identity,Proposed,"Historical identity of one bounded interaction episode under declared continuity, participant, boundary, and timescale criteria.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction,Interaction; Interaction Similarity; Comparative Interaction,,,,, type-identity,Type identity,Proposed,Membership in the same abstraction-defined interaction class under explicit classification rules.,,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction Similarity,Interaction Similarity; Interaction; Comparative Interaction,,,,, equivalence,Equivalence,Proposed,Exact preservation under a declared comparison contract and observable set. Equivalence is always typed.,,typed equivalence,,Interaction similarity,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction Similarity,"Interaction Similarity; Representation, Invariance, and Projection; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Comparative Interaction; Formal Models of Computational Interaction",,,,, similarity,Similarity,Proposed,"Graded proximity under declared dimensions, representations, alignment rules, metrics, weights, tolerances, and uncertainty.",,typed similarity,universal similarity score,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction Similarity,"Interaction Similarity; INTERACTION AS A SCIENTIFIC EXPLANANDUM; Foundations of Computational Interaction; Interaction Transfer; Predicting Interaction",,Similarity Contract,,, incomparability,Incomparability,Proposed,"Failure to establish a defensible common comparison space because boundaries, targets, mappings, scales, observation processes, uncertainty, or validity domains cannot be aligned without unsupported assumptions.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Comparative Interaction,Comparative Interaction; Interaction Similarity; Foundations of Computational Interaction,,,,, similarity-contract,Similarity contract,Proposed reusable artifact,"A declaration of comparison target, frame, representations, correspondence mapping, invariants, variants, observables, admissible and prohibited transformations, typed metrics or predicates, tolerances, uncertainty, validity domain, and final typed profile.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction Similarity,Interaction Similarity; Predicting Interaction,,Similarity Contract,Layered observation-enriched probabilistic labeled transition system,, strategy,Strategy,Proposed latent explanatory construct,"An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states.","A strategy is not a single action, raw trace, repeated sequence, explicit plan, policy alone, skill, habit, or intention. It must be supported through rival discrimination, diagnostic contingencies, uncertainty, and evidence appropriate to the claim.",,,Policy; Interaction history; Strategy contract,No - latent/inferred,Yes,Requires latent-variable model,Interaction Strategies,Interaction Strategies; Predicting Interaction; Interaction Transfer; Formal Models of Computational Interaction; Foundations of Computational Interaction,,Strategy Contract,Layered observation-enriched probabilistic labeled transition system,"An inferred pattern of conditional search, commitment, and recovery across episodes.",A single successful action labeled as a strategy. strategy-contract,Strategy contract,Proposed reusable artifact,"A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain.",,,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Interaction Strategies,Interaction Strategies,,Strategy Contract,,, policy,Policy,Proposed,"A conditional relation from represented states, observations, or beliefs to action distributions.","A policy may be one component of a strategy. Strategy may additionally include information acquisition, commitment, resource allocation, switching, recovery, and stopping rules.",,,,No - latent/inferred,Yes,Requires latent-variable model,Interaction Strategies,"Interaction Strategies; Opportunity, Affordance, and Action Availability; Formal Models of Computational Interaction; Behavior; Interaction Similarity",,,,, fundamental,Fundamental,Proposed research substrate,"A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected.","Fundamental is not the scientific theory, a philosophical ontology, proof of CIS, or a guarantee of shared human meaning.",,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?","CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?; How Sciences Define Their Objects; Representation, Invariance, and Projection; Predicting Interaction",,,,, computational-interaction-science,Foundations of Computational Interaction,Proposed research program; disciplinary autonomy unproven,"A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence. CIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines.",,CompInt,,,Conditional on observation model,No or not inherently,Measure only under declared operationalization,Foundations of Computational Interaction,Foundations of Computational Interaction; Predicting Interaction,,,,, ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Canonical_Vocabulary.md (235 lines, 25.0 KiB) ======================================================================== **Canonical Vocabulary** Version 1.0.0-integration.1 54 canonical records. The CSV/XLSX versions are the machine-readable systems of record. ------------------------------------------------------------------------------------------------------------------------------------------------------- canonical_id term maturity observable_status latent_status measurement_status originating_paper ----------------------------------- ----------------- -------------- ------------------------- --------------- -------------------- ------------------- domain-commitments Domain Proposed Conditional on No or not Measure only under Ontology, commitments observation model inherently declared Semantics, operationalization Representation, and Interpretation system-state System state Proposed Conditional on No or not Measure only under Opportunity, observation model inherently declared Affordance, and operationalization Action Availability semantic-assignment Semantic Proposed Conditional on No or not Measure only under Ontology, assignment observation model inherently declared Semantics, operationalization Representation, and Interpretation semantic-state Semantic state Proposed No - latent/inferred Yes Requires Ontology, latent-variable Semantics, model Representation, and Interpretation information Information Proposed Conditional on No or not Measure only under Ontology, observation model inherently declared Semantics, operationalization Representation, and Interpretation representation Representation Proposed Conditional on No or not Measure only under Representation, observation model inherently declared Invariance, and operationalization Projection projection Projection Proposed Conditional on No or not Measure only under Opportunity, analytical observation model inherently declared Affordance, and role operationalization Action Availability scoped-invariance Scoped invariance Proposed Conditional on No or not Measure only under Canonical glossary theory observation model inherently declared operationalization interpretation Interpretation Proposed No - latent/inferred Yes Requires Ontology, latent-variable Semantics, model Representation, and Interpretation interaction-participant Interaction Proposed Conditional on No or not Measure only under Canonical glossary participant observation model inherently declared operationalization agent Agent Proposed Conditional on No or not Measure only under Opportunity, subtype observation model inherently declared Affordance, and operationalization Action Availability environment Environment Proposed Conditional on No or not Measure only under Behavior observation model inherently declared operationalization affordance Affordance Established Conditional on No or not Measure only under Opportunity, external observation model inherently declared Affordance, and construct operationalization Action Availability opportunity Opportunity Proposed Conditional on No or not Measure only under Opportunity, coordination observation model inherently declared Affordance, and framework operationalization Action Availability opportunity-profile Opportunity Proposed Conditional on No or not Operationalizable by Representation, profile observation model inherently contract Invariance, and Projection capability Capability Proposed Conditional on No or not Measure only under Opportunity, observation model inherently declared Affordance, and operationalization Action Availability permission Permission Proposed Conditional on No or not Measure only under Opportunity, observation model inherently declared Affordance, and operationalization Action Availability enablement Enablement Proposed Conditional on No or not Measure only under Opportunity, observation model inherently declared Affordance, and operationalization Action Availability reachability Reachability Proposed Conditional on No or not Operationalizable by Opportunity, observation model inherently contract Affordance, and Action Availability exposure Exposure Proposed Conditional on No or not Operationalizable by Opportunity, observation model inherently contract Affordance, and Action Availability signaling Signaling Proposed Conditional on No or not Operationalizable by Opportunity, observation model inherently contract Affordance, and Action Availability discoverability Discoverability Proposed Conditional on No or not Operationalizable by Opportunity, observation model inherently contract Affordance, and Action Availability believed-action Believed action Proposed No - latent/inferred Yes Requires Opportunity, latent latent-variable Affordance, and variable model Action Availability action Action Proposed Conditional on No or not Measure only under Opportunity, observation model inherently declared Affordance, and operationalization Action Availability state-transition State transition Proposed Directly/Instrumentally No or not Measure only under Interaction inherently declared operationalization observation Observation Proposed Directly/Instrumentally No or not Measure only under Formal Models of inherently declared Computational operationalization Interaction situated-behavior Situated behavior Proposed Conditional on No or not Measure only under Canonical glossary observation model inherently declared operationalization behavioral-evidence Behavioral Candidate Directly/Instrumentally No or not Measure only under Behavior evidence inherently declared operationalization behavioral-equivalence Behavioral Candidate Conditional on No or not Measure only under Representation, equivalence observation model inherently declared Invariance, and operationalization Projection interactional-equivalence Interactional Candidate Conditional on No or not Measure only under INTERACTION AS A\ equivalence observation model inherently declared SCIENTIFIC operationalization EXPLANANDUM interaction Interaction Proposed Conditional on No or not Measure only under Interaction scientific observation model inherently declared target operationalization interaction-episode Interaction Proposed Conditional on No or not Operationalizable by Interaction episode canonical unit observation model inherently contract coupling Coupling Proposed Conditional on No or not Measure only under Interaction observation model inherently declared operationalization perturbation Perturbation Proposed Conditional on No or not Measure only under Interaction observation model inherently declared operationalization uptake Uptake Proposed Conditional on No or not Measure only under Interaction observation model inherently declared operationalization recurrence Recurrence Proposed Conditional on No or not Measure only under Interaction observation model inherently declared operationalization interaction-contract Interaction Proposed Conditional on No or not Measure only under Interaction contract reusable observation model inherently declared artifact operationalization interaction-morphology Interaction Candidate Conditional on No or not Measure only under Canonical glossary morphology observation model inherently declared operationalization interaction-grammar Interaction Candidate Conditional on No or not Measure only under CAN INTERACTION grammar observation model inherently declared BECOME A\ operationalization PRIMARY SCIENTIFIC OBJECT? interaction-history Interaction Candidate Conditional on No or not Measure only under INTERACTION AS A\ history observation model inherently declared SCIENTIFIC operationalization EXPLANANDUM trace Trace Proposed Directly/Instrumentally No or not Operationalizable by Interaction inherently contract Similarity measurement-contract Measurement Proposed Conditional on No or not Operationalizable by Measurement contract reusable observation model inherently contract artifact interaction-similarity Interaction Proposed typed Conditional on No or not Operationalizable by INTERACTION AS A\ similarity comparison observation model inherently contract SCIENTIFIC framework EXPLANANDUM token-identity Token identity Proposed Conditional on No or not Measure only under Interaction observation model inherently declared operationalization type-identity Type identity Proposed Conditional on No or not Measure only under Interaction observation model inherently declared Similarity operationalization equivalence Equivalence Proposed Conditional on No or not Measure only under Interaction observation model inherently declared Similarity operationalization similarity Similarity Proposed Conditional on No or not Measure only under Interaction observation model inherently declared Similarity operationalization incomparability Incomparability Proposed Conditional on No or not Measure only under Comparative observation model inherently declared Interaction operationalization similarity-contract Similarity Proposed Conditional on No or not Measure only under Interaction contract reusable observation model inherently declared Similarity artifact operationalization strategy Strategy Proposed No - latent/inferred Yes Requires Interaction latent latent-variable Strategies explanatory model construct strategy-contract Strategy contract Proposed Conditional on No or not Measure only under Interaction reusable observation model inherently declared Strategies artifact operationalization policy Policy Proposed No - latent/inferred Yes Requires Interaction latent-variable Strategies model fundamental Fundamental Proposed Conditional on No or not Measure only under CAN INTERACTION research observation model inherently declared BECOME A\ substrate operationalization PRIMARY SCIENTIFIC OBJECT? computational-interaction-science Computational Proposed Conditional on No or not Measure only under Computational Interaction research observation model inherently declared Interaction Science Science program; operationalization disciplinary autonomy unproven ------------------------------------------------------------------------------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/09_Indexes_and_Graphs/Indexes/Cross_Reference_Matrix.csv (973 lines, 157.4 KiB) ======================================================================== Concept ID,Concept,Paper ID,Paper,Mention Count,Role,Source Path domain-commitments,Domain commitments,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx domain-commitments,Domain commitments,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx domain-commitments,Domain commitments,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx domain-commitments,Domain commitments,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx domain-commitments,Domain commitments,05,"Ontology, Semantics, Representation, and Interpretation",3,Originating,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx domain-commitments,Domain commitments,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx domain-commitments,Domain commitments,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx domain-commitments,Domain commitments,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx domain-commitments,Domain commitments,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx domain-commitments,Domain commitments,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx domain-commitments,Domain commitments,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx domain-commitments,Domain commitments,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx domain-commitments,Domain commitments,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx domain-commitments,Domain commitments,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx domain-commitments,Domain commitments,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx domain-commitments,Domain commitments,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx system-state,System state,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx system-state,System state,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx system-state,System state,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx system-state,System state,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx system-state,System state,05,"Ontology, Semantics, Representation, and Interpretation",2,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx system-state,System state,06,"Opportunity, Affordance, and Action Availability",3,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx system-state,System state,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx system-state,System state,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx system-state,System state,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx system-state,System state,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx system-state,System state,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx system-state,System state,12,Interaction Strategies,1,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx system-state,System state,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx system-state,System state,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx system-state,System state,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx system-state,System state,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx semantic-assignment,Semantic assignment,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx semantic-assignment,Semantic assignment,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx semantic-assignment,Semantic assignment,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx semantic-assignment,Semantic assignment,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx semantic-assignment,Semantic assignment,05,"Ontology, Semantics, Representation, and Interpretation",2,Originating,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx semantic-assignment,Semantic assignment,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx semantic-assignment,Semantic assignment,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx semantic-assignment,Semantic assignment,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx semantic-assignment,Semantic assignment,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx semantic-assignment,Semantic assignment,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx semantic-assignment,Semantic assignment,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx semantic-assignment,Semantic assignment,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx semantic-assignment,Semantic assignment,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx semantic-assignment,Semantic assignment,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx semantic-assignment,Semantic assignment,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx semantic-assignment,Semantic assignment,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx semantic-state,Semantic state,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx semantic-state,Semantic state,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx semantic-state,Semantic state,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx semantic-state,Semantic state,04,"Representation, Invariance, and Projection",1,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx semantic-state,Semantic state,05,"Ontology, Semantics, Representation, and Interpretation",7,Originating,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx semantic-state,Semantic state,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx semantic-state,Semantic state,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx semantic-state,Semantic state,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx semantic-state,Semantic state,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx semantic-state,Semantic state,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx semantic-state,Semantic state,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx semantic-state,Semantic state,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx semantic-state,Semantic state,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx semantic-state,Semantic state,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx semantic-state,Semantic state,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx semantic-state,Semantic state,16,Foundations of Computational Interaction,1,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx information,Information,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",10,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx information,Information,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",10,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx information,Information,03,How Sciences Define Their Objects,2,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx information,Information,04,"Representation, Invariance, and Projection",24,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx information,Information,05,"Ontology, Semantics, Representation, and Interpretation",29,Originating,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx information,Information,06,"Opportunity, Affordance, and Action Availability",6,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx information,Information,07,Interaction,3,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx information,Information,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx information,Information,09,Measurement,4,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx information,Information,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx information,Information,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx information,Information,12,Interaction Strategies,21,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx information,Information,13,Formal Models of Computational Interaction,1,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx information,Information,14,Predicting Interaction,13,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx information,Information,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx information,Information,16,Foundations of Computational Interaction,3,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx representation,Representation,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",30,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx representation,Representation,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",4,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx representation,Representation,03,How Sciences Define Their Objects,6,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx representation,Representation,04,"Representation, Invariance, and Projection",60,Originating,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx representation,Representation,05,"Ontology, Semantics, Representation, and Interpretation",25,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx representation,Representation,06,"Opportunity, Affordance, and Action Availability",4,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx representation,Representation,07,Interaction,2,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx representation,Representation,08,Behavior,6,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx representation,Representation,09,Measurement,8,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx representation,Representation,10,Interaction Similarity,6,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx representation,Representation,11,Interaction Transfer,15,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx representation,Representation,12,Interaction Strategies,10,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx representation,Representation,13,Formal Models of Computational Interaction,5,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx representation,Representation,14,Predicting Interaction,3,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx representation,Representation,15,Comparative Interaction,3,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx representation,Representation,16,Foundations of Computational Interaction,12,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx projection,Projection,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx projection,Projection,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx projection,Projection,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx projection,Projection,04,"Representation, Invariance, and Projection",24,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx projection,Projection,05,"Ontology, Semantics, Representation, and Interpretation",5,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx projection,Projection,06,"Opportunity, Affordance, and Action Availability",32,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx projection,Projection,07,Interaction,2,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx projection,Projection,08,Behavior,3,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx projection,Projection,09,Measurement,6,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx projection,Projection,10,Interaction Similarity,2,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx projection,Projection,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx projection,Projection,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx projection,Projection,13,Formal Models of Computational Interaction,14,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx projection,Projection,14,Predicting Interaction,7,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx projection,Projection,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx projection,Projection,16,Foundations of Computational Interaction,10,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx scoped-invariance,Scoped invariance,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx scoped-invariance,Scoped invariance,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx scoped-invariance,Scoped invariance,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx scoped-invariance,Scoped invariance,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx scoped-invariance,Scoped invariance,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx scoped-invariance,Scoped invariance,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx scoped-invariance,Scoped invariance,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx scoped-invariance,Scoped invariance,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx scoped-invariance,Scoped invariance,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx scoped-invariance,Scoped invariance,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx scoped-invariance,Scoped invariance,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx scoped-invariance,Scoped invariance,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx scoped-invariance,Scoped invariance,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx scoped-invariance,Scoped invariance,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx scoped-invariance,Scoped invariance,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx scoped-invariance,Scoped invariance,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interpretation,Interpretation,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",20,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interpretation,Interpretation,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",3,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interpretation,Interpretation,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interpretation,Interpretation,04,"Representation, Invariance, and Projection",24,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interpretation,Interpretation,05,"Ontology, Semantics, Representation, and Interpretation",47,Originating,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interpretation,Interpretation,06,"Opportunity, Affordance, and Action Availability",6,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interpretation,Interpretation,07,Interaction,7,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interpretation,Interpretation,08,Behavior,4,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interpretation,Interpretation,09,Measurement,19,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interpretation,Interpretation,10,Interaction Similarity,2,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interpretation,Interpretation,11,Interaction Transfer,2,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interpretation,Interpretation,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interpretation,Interpretation,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interpretation,Interpretation,14,Predicting Interaction,3,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interpretation,Interpretation,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interpretation,Interpretation,16,Foundations of Computational Interaction,9,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-participant,Interaction participant,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-participant,Interaction participant,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-participant,Interaction participant,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-participant,Interaction participant,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-participant,Interaction participant,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx 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Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx affordance,Affordance,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx affordance,Affordance,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx affordance,Affordance,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx affordance,Affordance,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx affordance,Affordance,16,Foundations of Computational 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Transfer,8,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx opportunity,Opportunity,12,Interaction Strategies,14,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx opportunity,Opportunity,13,Formal Models of Computational Interaction,8,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx opportunity,Opportunity,14,Predicting Interaction,13,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx opportunity,Opportunity,15,Comparative Interaction,9,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx opportunity,Opportunity,16,Foundations of Computational Interaction,14,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx opportunity-profile,Opportunity profile,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx opportunity-profile,Opportunity profile,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx opportunity-profile,Opportunity profile,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx opportunity-profile,Opportunity profile,04,"Representation, Invariance, and Projection",1,Originating,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx opportunity-profile,Opportunity profile,05,"Ontology, Semantics, Representation, and 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Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx opportunity-profile,Opportunity profile,16,Foundations of Computational Interaction,1,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx capability,Capability,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",1,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx capability,Capability,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx capability,Capability,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx capability,Capability,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx capability,Capability,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx capability,Capability,06,"Opportunity, Affordance, and Action Availability",16,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx capability,Capability,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx capability,Capability,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx capability,Capability,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx capability,Capability,10,Interaction 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mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx capability,Capability,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx permission,Permission,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx permission,Permission,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx permission,Permission,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx permission,Permission,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx permission,Permission,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx permission,Permission,06,"Opportunity, Affordance, and Action Availability",13,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx permission,Permission,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx permission,Permission,08,Behavior,1,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx permission,Permission,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx permission,Permission,10,Interaction Similarity,1,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx permission,Permission,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx permission,Permission,12,Interaction Strategies,1,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx permission,Permission,13,Formal Models of Computational Interaction,1,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx permission,Permission,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx permission,Permission,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx permission,Permission,16,Foundations of Computational Interaction,3,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx enablement,Enablement,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx enablement,Enablement,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx enablement,Enablement,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx enablement,Enablement,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx enablement,Enablement,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx enablement,Enablement,06,"Opportunity, Affordance, and Action Availability",8,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx enablement,Enablement,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx enablement,Enablement,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx enablement,Enablement,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx enablement,Enablement,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx enablement,Enablement,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx enablement,Enablement,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx enablement,Enablement,13,Formal Models of Computational Interaction,1,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx enablement,Enablement,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx enablement,Enablement,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx enablement,Enablement,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx reachability,Reachability,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx reachability,Reachability,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx reachability,Reachability,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx reachability,Reachability,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx reachability,Reachability,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx reachability,Reachability,06,"Opportunity, Affordance, and Action Availability",14,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx reachability,Reachability,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx reachability,Reachability,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx reachability,Reachability,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx reachability,Reachability,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx reachability,Reachability,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx reachability,Reachability,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx reachability,Reachability,13,Formal Models of Computational Interaction,5,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx reachability,Reachability,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx reachability,Reachability,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx reachability,Reachability,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx exposure,Exposure,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",5,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx exposure,Exposure,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx exposure,Exposure,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx exposure,Exposure,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx exposure,Exposure,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx exposure,Exposure,06,"Opportunity, Affordance, and Action Availability",29,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx exposure,Exposure,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx exposure,Exposure,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx exposure,Exposure,09,Measurement,1,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx exposure,Exposure,10,Interaction 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Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx exposure,Exposure,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx signaling,Signaling,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx signaling,Signaling,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx signaling,Signaling,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx signaling,Signaling,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx signaling,Signaling,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx signaling,Signaling,06,"Opportunity, Affordance, and Action Availability",21,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx signaling,Signaling,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx signaling,Signaling,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx signaling,Signaling,09,Measurement,1,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx signaling,Signaling,10,Interaction Similarity,1,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx signaling,Signaling,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx signaling,Signaling,12,Interaction Strategies,1,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx signaling,Signaling,13,Formal Models of Computational Interaction,2,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx signaling,Signaling,14,Predicting Interaction,2,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx signaling,Signaling,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx signaling,Signaling,16,Foundations of Computational Interaction,3,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx discoverability,Discoverability,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx discoverability,Discoverability,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx discoverability,Discoverability,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx discoverability,Discoverability,04,"Representation, Invariance, and Projection",2,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx discoverability,Discoverability,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx discoverability,Discoverability,06,"Opportunity, Affordance, and Action Availability",7,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx discoverability,Discoverability,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx discoverability,Discoverability,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx discoverability,Discoverability,09,Measurement,4,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx discoverability,Discoverability,10,Interaction Similarity,1,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx discoverability,Discoverability,11,Interaction Transfer,2,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx discoverability,Discoverability,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx discoverability,Discoverability,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx discoverability,Discoverability,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx discoverability,Discoverability,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx discoverability,Discoverability,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx believed-action,Believed action,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",3,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx believed-action,Believed action,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx believed-action,Believed action,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx believed-action,Believed action,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx believed-action,Believed action,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx believed-action,Believed action,06,"Opportunity, Affordance, and Action Availability",5,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx believed-action,Believed action,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx believed-action,Believed action,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx believed-action,Believed action,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx believed-action,Believed action,10,Interaction Similarity,1,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx believed-action,Believed action,11,Interaction Transfer,1,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx believed-action,Believed action,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx believed-action,Believed action,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx believed-action,Believed action,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx believed-action,Believed action,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx believed-action,Believed action,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx action,Action,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",56,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx action,Action,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",25,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx action,Action,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx action,Action,04,"Representation, Invariance, and Projection",8,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx action,Action,05,"Ontology, Semantics, Representation, and Interpretation",11,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx action,Action,06,"Opportunity, Affordance, and Action Availability",68,Originating,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx action,Action,07,Interaction,18,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx action,Action,08,Behavior,19,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx action,Action,09,Measurement,4,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx action,Action,10,Interaction Similarity,5,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx action,Action,11,Interaction Transfer,3,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx action,Action,12,Interaction Strategies,35,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx action,Action,13,Formal Models of Computational Interaction,13,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx action,Action,14,Predicting Interaction,9,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx action,Action,15,Comparative Interaction,4,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx action,Action,16,Foundations of Computational Interaction,7,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx state-transition,State transition,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",1,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx state-transition,State transition,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx state-transition,State transition,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx state-transition,State transition,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx state-transition,State transition,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx state-transition,State transition,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx state-transition,State transition,07,Interaction,3,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx state-transition,State transition,08,Behavior,2,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx state-transition,State transition,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx state-transition,State transition,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx state-transition,State transition,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx state-transition,State transition,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx state-transition,State transition,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx state-transition,State transition,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx state-transition,State transition,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx state-transition,State transition,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx observation,Observation,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",11,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx observation,Observation,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",9,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx observation,Observation,03,How Sciences Define Their Objects,2,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx observation,Observation,04,"Representation, Invariance, and Projection",1,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx observation,Observation,05,"Ontology, Semantics, Representation, and Interpretation",2,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx observation,Observation,06,"Opportunity, Affordance, and Action Availability",6,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx observation,Observation,07,Interaction,5,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx observation,Observation,08,Behavior,9,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx observation,Observation,09,Measurement,12,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx observation,Observation,10,Interaction Similarity,10,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx observation,Observation,11,Interaction Transfer,1,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx observation,Observation,12,Interaction Strategies,11,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx observation,Observation,13,Formal Models of Computational Interaction,21,Originating,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx observation,Observation,14,Predicting Interaction,7,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx observation,Observation,15,Comparative Interaction,7,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx observation,Observation,16,Foundations of Computational Interaction,10,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx situated-behavior,Situated behavior,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx situated-behavior,Situated behavior,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx situated-behavior,Situated behavior,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx situated-behavior,Situated behavior,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx situated-behavior,Situated behavior,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx situated-behavior,Situated behavior,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx situated-behavior,Situated behavior,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx situated-behavior,Situated behavior,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx situated-behavior,Situated behavior,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx situated-behavior,Situated behavior,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx situated-behavior,Situated behavior,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx situated-behavior,Situated behavior,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx situated-behavior,Situated behavior,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx situated-behavior,Situated behavior,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx situated-behavior,Situated behavior,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx situated-behavior,Situated behavior,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx behavioral-evidence,Behavioral evidence,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",1,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx behavioral-evidence,Behavioral evidence,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx behavioral-evidence,Behavioral evidence,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx behavioral-evidence,Behavioral evidence,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx behavioral-evidence,Behavioral evidence,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx behavioral-evidence,Behavioral evidence,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx behavioral-evidence,Behavioral evidence,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx behavioral-evidence,Behavioral evidence,08,Behavior,3,Originating,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx behavioral-evidence,Behavioral evidence,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx behavioral-evidence,Behavioral evidence,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx behavioral-evidence,Behavioral evidence,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx behavioral-evidence,Behavioral evidence,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx behavioral-evidence,Behavioral evidence,13,Formal Models of Computational Interaction,1,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx behavioral-evidence,Behavioral evidence,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx behavioral-evidence,Behavioral evidence,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx behavioral-evidence,Behavioral evidence,16,Foundations of Computational Interaction,3,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx behavioral-equivalence,Behavioral equivalence,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx behavioral-equivalence,Behavioral equivalence,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx behavioral-equivalence,Behavioral equivalence,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx behavioral-equivalence,Behavioral equivalence,04,"Representation, Invariance, and Projection",4,Originating,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx behavioral-equivalence,Behavioral equivalence,05,"Ontology, Semantics, Representation, and Interpretation",1,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx behavioral-equivalence,Behavioral equivalence,06,"Opportunity, Affordance, and Action Availability",1,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx behavioral-equivalence,Behavioral equivalence,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx behavioral-equivalence,Behavioral equivalence,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx behavioral-equivalence,Behavioral equivalence,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx behavioral-equivalence,Behavioral equivalence,10,Interaction Similarity,3,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx behavioral-equivalence,Behavioral equivalence,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx behavioral-equivalence,Behavioral equivalence,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx behavioral-equivalence,Behavioral equivalence,13,Formal Models of Computational Interaction,2,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx behavioral-equivalence,Behavioral equivalence,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx behavioral-equivalence,Behavioral equivalence,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx behavioral-equivalence,Behavioral equivalence,16,Foundations of Computational Interaction,1,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interactional-equivalence,Interactional equivalence,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",2,Originating,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interactional-equivalence,Interactional equivalence,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interactional-equivalence,Interactional equivalence,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interactional-equivalence,Interactional equivalence,04,"Representation, Invariance, and Projection",2,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interactional-equivalence,Interactional equivalence,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interactional-equivalence,Interactional equivalence,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interactional-equivalence,Interactional equivalence,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interactional-equivalence,Interactional equivalence,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interactional-equivalence,Interactional equivalence,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interactional-equivalence,Interactional equivalence,10,Interaction Similarity,1,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interactional-equivalence,Interactional equivalence,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interactional-equivalence,Interactional equivalence,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interactional-equivalence,Interactional equivalence,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interactional-equivalence,Interactional equivalence,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interactional-equivalence,Interactional equivalence,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interactional-equivalence,Interactional equivalence,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction,Interaction,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",83,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction,Interaction,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",116,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction,Interaction,03,How Sciences Define Their Objects,17,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction,Interaction,04,"Representation, Invariance, and Projection",6,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction,Interaction,05,"Ontology, Semantics, Representation, and Interpretation",1,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction,Interaction,06,"Opportunity, Affordance, and Action Availability",7,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction,Interaction,07,Interaction,123,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction,Interaction,08,Behavior,20,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction,Interaction,09,Measurement,31,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction,Interaction,10,Interaction Similarity,30,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction,Interaction,11,Interaction Transfer,28,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction,Interaction,12,Interaction Strategies,19,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction,Interaction,13,Formal Models of Computational Interaction,21,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction,Interaction,14,Predicting Interaction,34,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction,Interaction,15,Comparative Interaction,28,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction,Interaction,16,Foundations of Computational Interaction,38,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-episode,Interaction episode,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-episode,Interaction episode,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",3,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-episode,Interaction episode,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-episode,Interaction episode,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-episode,Interaction episode,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-episode,Interaction episode,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-episode,Interaction episode,07,Interaction,5,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-episode,Interaction episode,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-episode,Interaction episode,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-episode,Interaction episode,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-episode,Interaction episode,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-episode,Interaction episode,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-episode,Interaction episode,13,Formal Models of Computational Interaction,3,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-episode,Interaction episode,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-episode,Interaction episode,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-episode,Interaction episode,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx coupling,Coupling,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",9,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx coupling,Coupling,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",18,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx coupling,Coupling,03,How Sciences Define Their Objects,2,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx coupling,Coupling,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx coupling,Coupling,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx coupling,Coupling,06,"Opportunity, Affordance, and Action Availability",1,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx coupling,Coupling,07,Interaction,36,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx coupling,Coupling,08,Behavior,1,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx coupling,Coupling,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx coupling,Coupling,10,Interaction Similarity,2,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx coupling,Coupling,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx coupling,Coupling,12,Interaction Strategies,2,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx coupling,Coupling,13,Formal Models of Computational Interaction,6,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx coupling,Coupling,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx coupling,Coupling,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx coupling,Coupling,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx perturbation,Perturbation,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",1,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx perturbation,Perturbation,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx perturbation,Perturbation,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx perturbation,Perturbation,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx perturbation,Perturbation,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx perturbation,Perturbation,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx perturbation,Perturbation,07,Interaction,9,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx perturbation,Perturbation,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx perturbation,Perturbation,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx perturbation,Perturbation,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx perturbation,Perturbation,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx perturbation,Perturbation,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx perturbation,Perturbation,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx perturbation,Perturbation,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx perturbation,Perturbation,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx perturbation,Perturbation,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx uptake,Uptake,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx uptake,Uptake,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx uptake,Uptake,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx uptake,Uptake,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx uptake,Uptake,05,"Ontology, Semantics, Representation, and Interpretation",1,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx uptake,Uptake,06,"Opportunity, Affordance, and Action Availability",1,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx uptake,Uptake,07,Interaction,11,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx uptake,Uptake,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx uptake,Uptake,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx uptake,Uptake,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx uptake,Uptake,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx uptake,Uptake,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx uptake,Uptake,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx uptake,Uptake,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx uptake,Uptake,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx uptake,Uptake,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx recurrence,Recurrence,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx recurrence,Recurrence,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx recurrence,Recurrence,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx recurrence,Recurrence,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx recurrence,Recurrence,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx recurrence,Recurrence,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx recurrence,Recurrence,07,Interaction,9,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx recurrence,Recurrence,08,Behavior,1,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx recurrence,Recurrence,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx recurrence,Recurrence,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx recurrence,Recurrence,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx recurrence,Recurrence,12,Interaction Strategies,2,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx recurrence,Recurrence,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx recurrence,Recurrence,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx recurrence,Recurrence,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx recurrence,Recurrence,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-contract,Interaction contract,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-contract,Interaction contract,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-contract,Interaction contract,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-contract,Interaction contract,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-contract,Interaction contract,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-contract,Interaction contract,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-contract,Interaction contract,07,Interaction,3,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-contract,Interaction contract,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-contract,Interaction contract,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-contract,Interaction contract,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-contract,Interaction contract,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-contract,Interaction contract,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-contract,Interaction contract,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-contract,Interaction contract,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-contract,Interaction contract,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-contract,Interaction contract,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-morphology,Interaction morphology,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-morphology,Interaction morphology,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-morphology,Interaction morphology,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-morphology,Interaction morphology,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-morphology,Interaction morphology,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-morphology,Interaction morphology,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-morphology,Interaction morphology,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-morphology,Interaction morphology,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-morphology,Interaction morphology,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-morphology,Interaction morphology,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-morphology,Interaction morphology,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-morphology,Interaction morphology,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-morphology,Interaction morphology,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-morphology,Interaction morphology,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-morphology,Interaction morphology,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-morphology,Interaction morphology,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-grammar,Interaction grammar,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-grammar,Interaction grammar,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",1,Originating,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-grammar,Interaction grammar,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-grammar,Interaction grammar,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-grammar,Interaction grammar,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-grammar,Interaction grammar,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-grammar,Interaction grammar,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-grammar,Interaction grammar,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-grammar,Interaction grammar,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-grammar,Interaction grammar,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-grammar,Interaction grammar,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-grammar,Interaction grammar,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-grammar,Interaction grammar,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-grammar,Interaction grammar,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-grammar,Interaction grammar,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-grammar,Interaction grammar,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-history,Interaction history,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",3,Originating,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-history,Interaction history,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-history,Interaction history,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-history,Interaction history,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-history,Interaction history,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-history,Interaction history,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-history,Interaction history,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-history,Interaction history,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-history,Interaction history,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-history,Interaction history,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-history,Interaction history,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-history,Interaction history,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-history,Interaction history,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-history,Interaction history,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-history,Interaction history,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-history,Interaction history,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx trace,Trace,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",3,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx trace,Trace,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx trace,Trace,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx trace,Trace,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx trace,Trace,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx trace,Trace,06,"Opportunity, Affordance, and Action Availability",3,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx trace,Trace,07,Interaction,5,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx trace,Trace,08,Behavior,14,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx trace,Trace,09,Measurement,1,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx trace,Trace,10,Interaction Similarity,20,Originating,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx trace,Trace,11,Interaction Transfer,1,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx trace,Trace,12,Interaction Strategies,8,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx trace,Trace,13,Formal Models of Computational Interaction,4,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx trace,Trace,14,Predicting Interaction,5,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx trace,Trace,15,Comparative Interaction,5,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx trace,Trace,16,Foundations of Computational Interaction,4,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx measurement-contract,Measurement contract,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx measurement-contract,Measurement contract,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx measurement-contract,Measurement contract,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx measurement-contract,Measurement contract,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx measurement-contract,Measurement contract,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx measurement-contract,Measurement contract,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx measurement-contract,Measurement contract,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx measurement-contract,Measurement contract,08,Behavior,1,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx measurement-contract,Measurement contract,09,Measurement,4,Originating,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx measurement-contract,Measurement contract,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx measurement-contract,Measurement contract,11,Interaction Transfer,1,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx measurement-contract,Measurement contract,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx measurement-contract,Measurement contract,13,Formal Models of Computational Interaction,3,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx measurement-contract,Measurement contract,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx measurement-contract,Measurement contract,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx measurement-contract,Measurement contract,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx interaction-similarity,Interaction similarity,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",2,Originating,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx interaction-similarity,Interaction similarity,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx interaction-similarity,Interaction similarity,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx interaction-similarity,Interaction similarity,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx interaction-similarity,Interaction similarity,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx interaction-similarity,Interaction similarity,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx interaction-similarity,Interaction similarity,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx interaction-similarity,Interaction similarity,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx interaction-similarity,Interaction similarity,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx interaction-similarity,Interaction similarity,10,Interaction Similarity,2,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx interaction-similarity,Interaction similarity,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx interaction-similarity,Interaction similarity,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx interaction-similarity,Interaction similarity,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx interaction-similarity,Interaction similarity,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx interaction-similarity,Interaction similarity,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx interaction-similarity,Interaction similarity,16,Foundations of Computational Interaction,1,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx token-identity,Token identity,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx token-identity,Token identity,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx token-identity,Token identity,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx token-identity,Token identity,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx token-identity,Token identity,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx token-identity,Token identity,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx token-identity,Token identity,07,Interaction,2,Originating,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx token-identity,Token identity,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx token-identity,Token identity,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx token-identity,Token identity,10,Interaction Similarity,2,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx token-identity,Token identity,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx token-identity,Token identity,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx token-identity,Token identity,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx token-identity,Token identity,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx token-identity,Token identity,15,Comparative Interaction,2,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx token-identity,Token identity,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx type-identity,Type identity,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx type-identity,Type identity,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx type-identity,Type identity,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx type-identity,Type identity,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx type-identity,Type identity,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx type-identity,Type identity,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx type-identity,Type identity,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx type-identity,Type identity,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx type-identity,Type identity,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx type-identity,Type identity,10,Interaction Similarity,2,Originating,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx type-identity,Type identity,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx type-identity,Type identity,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx type-identity,Type identity,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx type-identity,Type identity,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx type-identity,Type identity,15,Comparative Interaction,1,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx type-identity,Type identity,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx equivalence,Equivalence,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",19,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx equivalence,Equivalence,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",2,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx equivalence,Equivalence,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx equivalence,Equivalence,04,"Representation, Invariance, and Projection",31,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx equivalence,Equivalence,05,"Ontology, Semantics, Representation, and Interpretation",5,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx equivalence,Equivalence,06,"Opportunity, Affordance, and Action Availability",8,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx equivalence,Equivalence,07,Interaction,6,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx equivalence,Equivalence,08,Behavior,3,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx equivalence,Equivalence,09,Measurement,6,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx equivalence,Equivalence,10,Interaction Similarity,46,Originating,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx equivalence,Equivalence,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx equivalence,Equivalence,12,Interaction Strategies,3,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx equivalence,Equivalence,13,Formal Models of Computational Interaction,11,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx equivalence,Equivalence,14,Predicting Interaction,2,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx equivalence,Equivalence,15,Comparative Interaction,16,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx equivalence,Equivalence,16,Foundations of Computational Interaction,6,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx similarity,Similarity,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",6,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx similarity,Similarity,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx similarity,Similarity,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx similarity,Similarity,04,"Representation, Invariance, and Projection",4,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx similarity,Similarity,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx similarity,Similarity,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx similarity,Similarity,07,Interaction,1,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx similarity,Similarity,08,Behavior,2,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx similarity,Similarity,09,Measurement,1,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx similarity,Similarity,10,Interaction Similarity,51,Originating,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx similarity,Similarity,11,Interaction Transfer,5,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx similarity,Similarity,12,Interaction Strategies,1,Supporting,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx similarity,Similarity,13,Formal Models of Computational Interaction,2,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx similarity,Similarity,14,Predicting Interaction,5,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx similarity,Similarity,15,Comparative Interaction,4,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx similarity,Similarity,16,Foundations of Computational Interaction,6,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx incomparability,Incomparability,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx incomparability,Incomparability,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx incomparability,Incomparability,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx incomparability,Incomparability,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx incomparability,Incomparability,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx incomparability,Incomparability,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx incomparability,Incomparability,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx incomparability,Incomparability,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx incomparability,Incomparability,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx incomparability,Incomparability,10,Interaction Similarity,5,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx incomparability,Incomparability,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx incomparability,Incomparability,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx incomparability,Incomparability,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx incomparability,Incomparability,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx incomparability,Incomparability,15,Comparative Interaction,7,Originating,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx incomparability,Incomparability,16,Foundations of Computational Interaction,2,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx similarity-contract,Similarity contract,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx similarity-contract,Similarity contract,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx similarity-contract,Similarity contract,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx similarity-contract,Similarity contract,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx similarity-contract,Similarity contract,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx similarity-contract,Similarity contract,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx similarity-contract,Similarity contract,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx similarity-contract,Similarity contract,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx similarity-contract,Similarity contract,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx similarity-contract,Similarity contract,10,Interaction Similarity,2,Originating,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx similarity-contract,Similarity contract,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx similarity-contract,Similarity contract,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx similarity-contract,Similarity contract,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx similarity-contract,Similarity contract,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx similarity-contract,Similarity contract,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx similarity-contract,Similarity contract,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx strategy,Strategy,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",6,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx strategy,Strategy,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",2,Supporting,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx strategy,Strategy,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx strategy,Strategy,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx strategy,Strategy,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx strategy,Strategy,06,"Opportunity, Affordance, and Action Availability",4,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx strategy,Strategy,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx strategy,Strategy,08,Behavior,4,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx strategy,Strategy,09,Measurement,4,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx strategy,Strategy,10,Interaction Similarity,6,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx strategy,Strategy,11,Interaction Transfer,12,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx strategy,Strategy,12,Interaction Strategies,102,Originating,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx strategy,Strategy,13,Formal Models of Computational Interaction,10,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx strategy,Strategy,14,Predicting Interaction,14,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx strategy,Strategy,15,Comparative Interaction,5,Supporting,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx strategy,Strategy,16,Foundations of Computational Interaction,8,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx strategy-contract,Strategy contract,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx strategy-contract,Strategy contract,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx strategy-contract,Strategy contract,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx strategy-contract,Strategy contract,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx strategy-contract,Strategy contract,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx strategy-contract,Strategy contract,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx strategy-contract,Strategy contract,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx strategy-contract,Strategy contract,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx strategy-contract,Strategy contract,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx strategy-contract,Strategy contract,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx strategy-contract,Strategy contract,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx strategy-contract,Strategy contract,12,Interaction Strategies,3,Originating,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx strategy-contract,Strategy contract,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx strategy-contract,Strategy contract,14,Predicting Interaction,0,No direct mention,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx strategy-contract,Strategy contract,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx strategy-contract,Strategy contract,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx policy,Policy,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",5,Supporting,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx policy,Policy,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx policy,Policy,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx policy,Policy,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx policy,Policy,05,"Ontology, Semantics, Representation, and Interpretation",4,Supporting,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx policy,Policy,06,"Opportunity, Affordance, and Action Availability",14,Supporting,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx policy,Policy,07,Interaction,2,Supporting,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx policy,Policy,08,Behavior,10,Supporting,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx policy,Policy,09,Measurement,1,Supporting,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx policy,Policy,10,Interaction Similarity,7,Supporting,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx policy,Policy,11,Interaction Transfer,6,Supporting,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx policy,Policy,12,Interaction Strategies,26,Originating,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx policy,Policy,13,Formal Models of Computational Interaction,12,Supporting,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx policy,Policy,14,Predicting Interaction,6,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx policy,Policy,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx policy,Policy,16,Foundations of Computational Interaction,1,Supporting,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx fundamental,Fundamental,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx fundamental,Fundamental,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",3,Originating,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx fundamental,Fundamental,03,How Sciences Define Their Objects,1,Supporting,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx fundamental,Fundamental,04,"Representation, Invariance, and Projection",1,Supporting,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx fundamental,Fundamental,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx fundamental,Fundamental,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx fundamental,Fundamental,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx fundamental,Fundamental,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx fundamental,Fundamental,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx fundamental,Fundamental,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx fundamental,Fundamental,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx fundamental,Fundamental,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx fundamental,Fundamental,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx fundamental,Fundamental,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx fundamental,Fundamental,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx fundamental,Fundamental,16,Foundations of Computational Interaction,0,No direct mention,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx computational-interaction-science,Foundations of Computational Interaction,01,"INTERACTION AS A SCIENTIFIC EXPLANANDUM",0,No direct mention,02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx computational-interaction-science,Foundations of Computational Interaction,02,"CAN INTERACTION BECOME A PRIMARY SCIENTIFIC OBJECT?",0,No direct mention,02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx computational-interaction-science,Foundations of Computational Interaction,03,How Sciences Define Their Objects,0,No direct mention,02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx computational-interaction-science,Foundations of Computational Interaction,04,"Representation, Invariance, and Projection",0,No direct mention,02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx computational-interaction-science,Foundations of Computational Interaction,05,"Ontology, Semantics, Representation, and Interpretation",0,No direct mention,02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.docx computational-interaction-science,Foundations of Computational Interaction,06,"Opportunity, Affordance, and Action Availability",0,No direct mention,02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx computational-interaction-science,Foundations of Computational Interaction,07,Interaction,0,No direct mention,02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.docx computational-interaction-science,Foundations of Computational Interaction,08,Behavior,0,No direct mention,02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.docx computational-interaction-science,Foundations of Computational Interaction,09,Measurement,0,No direct mention,02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.docx computational-interaction-science,Foundations of Computational Interaction,10,Interaction Similarity,0,No direct mention,02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx computational-interaction-science,Foundations of Computational Interaction,11,Interaction Transfer,0,No direct mention,02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx computational-interaction-science,Foundations of Computational Interaction,12,Interaction Strategies,0,No direct mention,02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx computational-interaction-science,Foundations of Computational Interaction,13,Formal Models of Computational Interaction,0,No direct mention,02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx computational-interaction-science,Foundations of Computational Interaction,14,Predicting Interaction,1,Supporting,02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx computational-interaction-science,Foundations of Computational Interaction,15,Comparative Interaction,0,No direct mention,02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx computational-interaction-science,Foundations of Computational Interaction,16,Foundations of Computational Interaction,5,Originating,02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/Consent_Governance.md (17 lines, 0.9 KiB) ======================================================================== # Consent Governance 0.1.0 Every participant dataset references an immutable consent record conforming to `consent-record.schema.json`. Consent scope declares study participation, recording modalities, data categories, retention, future reuse, sharing, publication, recontact, withdrawal, and any automated or AI-assisted processing. Amendments create a new consent version and append a relationship to the prior version; they never overwrite it. Published releases freeze the applicable version. Withdrawal creates a new `withdrawn` record and triggers the study data management disposition process. Sensitive cultural, community, institutional, or collective contexts may require authority beyond individual consent. The study must record the relevant community review, decision scope, dissent, benefit/risk distribution, reuse limits, and continuing contact. Consent never converts an unnecessary or disproportionate collection into an acceptable one. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/Ethics_and_Power_Gates.md (24 lines, 1.6 KiB) ======================================================================== # Ethics and Power Gates 0.1.0 These gates are non-compensatory: a favorable aggregate score cannot offset a failed gate. | Gate | Pass condition | Required record | |---|---|---| | coercion | refusal and withdrawal are practically available without disproportionate penalty | recruitment and withdrawal review | | manipulation | influence mechanisms, deception, and debriefing are reviewed and bounded | manipulation inventory | | exclusion and accessibility | required participants can access the task or exclusions are justified and reported | accessibility and exclusion audit | | authority and institutional power | permissions, decision rights, and appeal paths are explicit | authority map | | asymmetric risk | burdens and irreversible harms are not shifted onto less powerful groups | distributional risk review | | subgroup preservation | no aggregate decision hides a failed subgroup gate | subgroup evidence record | | cultural claim | context provenance is recorded and essentialist inference is prohibited | community review or limitation statement | | reversibility | irreversible consequences have prevention, escalation, and remedy | harm and recovery plan | Any failed or unassessed applicable gate vetoes a comparative recommendation, deployment claim, or public release until the responsible review authority records a resolution. The Comparison Contract must reference this record when human or community consequences are in scope. Gate assessments are recorded against `ethics-gate-assessment.schema.json`, which requires all eight gates to be present and requires a resolution reference for any gate that is failed or unassessed. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/Participant_Data_Management_Plan.md (51 lines, 2.5 KiB) ======================================================================== # Participant Data Management Plan 0.1.0 **Status:** required template; no study is authorized by this document alone Frozen study-specific instances are recorded against `data-management-plan.schema.json`. ## Study declaration Before collection, freeze a study-specific instance naming the responsible owner, review authority, protocol and consent versions, participant population, purpose, data categories, instruments, storage locations, processors, access roles, retention dates, deletion mechanism, export rules, reuse scope, incident contact, and approved exceptions. ## Required controls - Minimize: collect only fields justified by a frozen outcome or governance requirement. Full prompts, direct identifiers, protected attributes, free-form sensitive text, and precise location are prohibited unless specifically approved and necessary. - Pseudonymize: keep the re-identification key in a separately controlled store; research records use a study-local participant reference. - Separate: isolate sensitive context, consent records, contact data, raw instrument records, coded events, analysis data, and public derivatives. - Authorize: deny access by default, use named roles, review grants, and remove access at role change or study close. - Retain and delete: declare calendar dates or events for every data class. Deletion must cover primary, derivative, export, and backup handling, with an auditable disposition record. - Export and reuse: log recipient, purpose, fields, transformations, agreement, consent basis, and expiration. New use outside consent or authority requires review before transfer. - Audit: record access to sensitive data, exports, transformations, consent amendments, withdrawals, incidents, and deletions without logging the sensitive payload itself. ## Withdrawal and correction Consent withdrawal is append-only. Record time, consent version, requested scope, affected data classes, disposition, exceptions required by approved policy, and completion. Never overwrite the original consent record. Link corrections and exclusions to retained provenance so published analyses can report their effect. ## Incident response Stop affected collection or export, contain access, preserve minimal forensic records, notify the responsible authority, assess participant and community impact, apply required notification, remediate, and record closure. Credentials, direct identifiers, full prompts, and raw sensitive payloads must not appear in incident tickets or routine logs. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/README.md (39 lines, 2.1 KiB) ======================================================================== # Research Governance Minimum This directory defines the minimum operational controls for FCI studies. It does not replace institutional, legal, ethical-review, accessibility, security, or community-specific requirements. Before collection, a study must record responsible owner, review authority, purpose, lawful/ethical basis, consent or approved alternative, participant population, data inventory, access roles, retention/deletion schedule, export and reuse terms, incident contact, and protocol-deviation procedure. ## Data controls - collect only fields required by the frozen protocol; - separate direct identifiers from research records and use study-local keys; - deny access by default and review access periodically; - encrypt transfers and protected storage using institution-approved controls; - log exports, transformations, deletions, and access to sensitive records; - prohibit raw sensitive records in examples, logs, prompts, and public bundles; - honor withdrawal, correction, deletion, and reuse terms defined by the study; - review subgroup, accessibility, and community harms before release. ## Machine-checkable instruments Governance records validate against draft-2020-12 JSON Schemas in this directory: - `consent-record.schema.json` — per-participant consent, amendment, and withdrawal records. - `ethics-gate-assessment.schema.json` — the eight non-compensatory ethics and power gates; any applicable gate that is failed or unassessed requires a recorded resolution before release. - `data-management-plan.schema.json` — the frozen, study-specific instance of the Participant Data Management Plan. Schema validation checks structure only; it does not establish that a study's controls, consent, or gate resolutions are substantively adequate. ## Incident and deviation handling Contain exposure, preserve an audit record, notify the responsible authority, assess participant impact, and document remediation. Protocol deviations must state when, why, affected records, analytical consequence, authorization, and whether collection or analysis was paused. They must never be hidden by editing the frozen contract in place. ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/consent-record.schema.json (38 lines, 1.5 KiB) ======================================================================== { "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "consent-record.schema.json", "title": "Computational Interaction Consent Record", "type": "object", "additionalProperties": false, "required": [ "record_id", "schema_version", "participant_ref", "protocol_ref", "consent_version", "recorded_at", "status", "permitted_uses", "retention_rule", "withdrawal_process", "future_reuse" ], "properties": { "record_id": { "type": "string", "minLength": 1 }, "schema_version": { "const": "0.2.0" }, "participant_ref": { "type": "string", "minLength": 1 }, "protocol_ref": { "type": "string", "minLength": 1 }, "consent_version": { "type": "string", "minLength": 1 }, "recorded_at": { "type": "string", "format": "date-time" }, "status": { "enum": ["granted", "declined", "withdrawn", "waived-by-authority"] }, "permitted_uses": { "type": "array", "items": { "type": "string" }, "uniqueItems": true }, "retention_rule": { "type": "string", "minLength": 1 }, "withdrawal_process": { "type": "string", "minLength": 1 }, "future_reuse": { "enum": ["not_permitted", "study_only", "specified_reuse", "broad_reuse"] }, "withdrawn_at": { "type": ["string", "null"], "format": "date-time" }, "authority_ref": { "type": ["string", "null"] }, "community_review_ref": { "type": ["string", "null"] }, "amends_record_id": { "type": ["string", "null"] }, "notes": { "type": ["string", "null"] } } } ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/data-management-plan.schema.json (126 lines, 4.9 KiB) ======================================================================== { "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "data-management-plan.schema.json", "title": "Foundations of Computational Interaction Participant Data Management Plan", "description": "A frozen, study-specific instance of the Participant Data Management Plan (Participant_Data_Management_Plan.md). No study is authorized by the plan template alone; this instance must be frozen before collection. Controls are recorded as explicit attestations rather than defaults, so an unattested control reads as not-satisfied.", "type": "object", "additionalProperties": false, "required": [ "record_id", "schema_version", "study_ref", "frozen_at", "responsible_owner", "review_authority", "protocol_version", "consent_version", "participant_population", "purpose", "data_categories", "retention", "reuse_scope", "incident_contact", "controls" ], "properties": { "record_id": { "type": "string", "minLength": 1 }, "schema_version": { "const": "0.1.0" }, "study_ref": { "type": "string", "minLength": 1 }, "frozen_at": { "type": "string", "format": "date-time" }, "responsible_owner": { "type": "string", "minLength": 1 }, "review_authority": { "type": "string", "minLength": 1 }, "protocol_version": { "type": "string", "minLength": 1 }, "consent_version": { "type": "string", "minLength": 1 }, "participant_population": { "type": "string", "minLength": 1 }, "purpose": { "type": "string", "minLength": 1 }, "data_categories": { "type": "array", "minItems": 1, "uniqueItems": true, "items": { "type": "string", "minLength": 1 }, "description": "Declared classes of data collected. Full prompts, direct identifiers, protected attributes, free-form sensitive text, and precise location are prohibited unless named here as specifically approved and necessary." }, "instruments": { "type": "array", "items": { "type": "string", "minLength": 1 } }, "storage_locations": { "type": "array", "items": { "type": "string", "minLength": 1 } }, "processors": { "type": "array", "items": { "type": "string", "minLength": 1 } }, "access_roles": { "type": "array", "items": { "type": "string", "minLength": 1 }, "description": "Named roles authorized under deny-by-default access." }, "retention": { "type": "array", "minItems": 1, "description": "A retention and deletion rule for every declared data class.", "items": { "type": "object", "additionalProperties": false, "required": ["data_class", "basis", "delete_by", "deletion_mechanism"], "properties": { "data_class": { "type": "string", "minLength": 1 }, "basis": { "type": "string", "minLength": 1, "description": "Frozen outcome or governance requirement justifying retention." }, "delete_by": { "type": "string", "minLength": 1, "description": "Calendar date or named triggering event." }, "deletion_mechanism": { "type": "string", "minLength": 1, "description": "Must cover primary, derivative, export, and backup handling, with an auditable disposition record." } } } }, "export_rules": { "type": ["string", "null"], "description": "Logging of recipient, purpose, fields, transformations, agreement, consent basis, and expiration for any export." }, "reuse_scope": { "enum": ["not_permitted", "study_only", "specified_reuse", "broad_reuse"], "description": "Aligned with the consent record's future_reuse enum. New use outside consent or authority requires review before transfer." }, "incident_contact": { "type": "string", "minLength": 1 }, "approved_exceptions": { "type": "array", "items": { "type": "string", "minLength": 1 } }, "controls": { "type": "object", "additionalProperties": false, "description": "Explicit attestation for each required control. Every control must be attested true for a plan to be complete.", "required": [ "minimize", "pseudonymize", "separate", "authorize", "retain_and_delete", "export_and_reuse_logged", "audit" ], "properties": { "minimize": { "const": true }, "pseudonymize": { "const": true }, "separate": { "const": true }, "authorize": { "const": true }, "retain_and_delete": { "const": true }, "export_and_reuse_logged": { "const": true }, "audit": { "const": true } } }, "withdrawal_process": { "type": ["string", "null"], "description": "Append-only withdrawal handling; original consent records are never overwritten." }, "notes": { "type": ["string", "null"] } } } ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/10_Governance/ethics-gate-assessment.schema.json (113 lines, 4.5 KiB) ======================================================================== { "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "ethics-gate-assessment.schema.json", "title": "Foundations of Computational Interaction Ethics and Power Gate Assessment", "description": "A non-compensatory assessment record for the eight ethics and power gates defined in Ethics_and_Power_Gates.md. A favorable aggregate score cannot offset a failed gate: every applicable gate that is failed or unassessed vetoes a comparative recommendation, deployment claim, or public release until the responsible review authority records a resolution. 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Required (non-null) when status is fail or unassessed, because such a gate otherwise vetoes release." } }, "allOf": [ { "if": { "properties": { "status": { "enum": ["fail", "unassessed"] } }, "required": ["status"] }, "then": { "required": ["resolution_ref"], "properties": { "resolution_ref": { "type": "string", "minLength": 1 } } } }, { "if": { "properties": { "status": { "const": "not_applicable" } }, "required": ["status"] }, "then": { "required": ["not_applicable_justification"], "properties": { "not_applicable_justification": { "type": "string", "minLength": 1 } } } } ] } } } ======================================================================== ## FILE: docs/01_Knowledge_System_of_Record/README.md (15 lines, 0.6 KiB) ======================================================================== # Knowledge System of Record Version: 1.0.0-structure.1 This directory is the canonical ownership layer for ontology, glossary, encyclopedia, framework, specifications, graphs, and reviews. Research papers provide evidence and provenance; they do not silently redefine canonical concepts. ## Authority order 1. Ratified specifications (none yet; Contracts consolidation is derivative) 2. Current ontology and glossary candidates 3. Program framework and encyclopedia 4. Research papers 5. Archived drafts and reviews No source document content was edited during this structural release. ======================================================================== ## FILE: docs/02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.md (2397 lines, 109.6 KiB) ======================================================================== **INTERACTION AS A\ SCIENTIFIC EXPLANANDUM** Boundary review, minimum ontology, and discipline test +-----------------------------------------------------------------------+ | **DECISION** | | | | **Do not create an independent discipline at present.** | | | | The evidence supports a focused interdisciplinary research program | | within HCI, tested against strong baselines from existing fields. | +=======================================================================+ +-----------------------------------------------------------------------+ **Research report** 15 July 2026 Scope: human interaction with computational processes, independent of any particular platform or implementation # Contents Executive decision 1\. Research question and decision standard 2\. Scope and core explanandum 3\. Method and evidential basis 4\. Literature review and explanatory boundaries 5\. Critique of the current working direction 6\. Recommended terminology 7\. Canonical ontology 8\. Foundational assumptions 9\. First principles 10\. Relationships among concepts 11\. Minimum formal model 12\. Smallest meaningful unit of interaction 13\. What constitutes evidence in interaction research 14\. Universals, acquisitions, and population variation 15\. Learning, adaptation, and transfer 16\. Representation, meaning, and visual structure 17\. Falsifiability and decisive tests 18\. Recommended sequence for foundational papers 19\. Formal argument 20\. Final conclusion 21\. Limitations References *Section numbering follows the report. Page numbers are shown in the footer.* # Executive decision **Decision: do not create an independent scientific discipline at present.** Human interaction with computational systems is a coherent explanandum, but the candidate mechanisms are already substantially covered by Human-Computer Interaction (HCI), cognitive science and psychology, human factors and cognitive systems engineering, ecological psychology, situated action, distributed cognition, activity theory, learning science, semiotics, information visualization, cybernetics, and computational interaction. The unresolved problem is integration: building and testing a representation-aware, context-conditioned, longitudinal model that connects these existing mechanisms across time scales. That problem justifies a focused interdisciplinary research program inside HCI, not a new discipline. The conclusion is conditional rather than permanent. A separate discipline would become scientifically justified only if a research program demonstrated all of the following: - persistent cross-domain phenomena that strong combinations of existing theories cannot explain; - at least one indispensable and operationalizable mechanism not reducible to established constructs; - replicated out-of-sample predictive improvement across systems, tasks, modalities, populations, and cultures; - a cumulative ontology and measurement program that remains stable when particular implementations disappear; - distinctive methods or evidence standards required by the explanandum rather than by institutional preference. Current literature does not meet those conditions. It instead shows theoretical pluralism, terminological fragmentation, and weak integration. Those are real scientific problems, but fragmentation alone is not evidence of a new natural kind or a new discipline. ## Recommended institutional form Use **foundational human-computational interaction research** as a descriptive program name, not as a disciplinary claim. Place it within HCI and connect it explicitly to cognitive science, human factors, learning science, and social theory. Avoid introducing a new field name until the proposed benchmark program produces evidence of conceptual irreducibility and incremental explanatory power. ## Minimum theoretical contribution The minimum useful contribution is not a new vocabulary. It is a shared integration contract consisting of: 1. a canonical ontology that distinguishes agents, state, representation, interpretation, action opportunities, actions, transitions, feedback, learned state, context, and evidence; 2. typed equivalence relations that prevent semantic, informational, computational, task, and interaction equivalence from being conflated; 3. a context-complete interaction record that makes behavioral traces interpretable relative to available and perceived alternatives; 4. a coupled, partially observed, longitudinal model that permits existing theories to be compared rather than rhetorically combined; 5. decisive falsification and model-comparison tests against a strong baseline assembled from existing disciplines. # 1. Research question and decision standard The central question is not whether interaction is important, complex, or under-theorized. It is whether interaction with computational systems constitutes an explanandum whose mechanisms cannot be adequately developed within existing disciplines. A scientific discipline is justified here only if it adds explanatory capacity, not merely a community, journal, curriculum, or label. The decision therefore uses five tests. ## 1.1 Discipline-necessity tests **Test 1 - Domain coherence.** Is there a stable class of phenomena that can be identified independently of particular products and implementations? **Test 2 - Conceptual irreducibility.** Does explaining that class require constructs or mechanisms that cannot be expressed adequately in established terms? **Test 3 - Predictive increment.** Do the proposed additions improve prediction, retrodiction, intervention, or transfer over a strong composite baseline from existing theories? **Test 4 - Methodological necessity.** Does the explanandum require distinctive forms of evidence or method rather than ordinary combinations of experimentation, field study, modeling, simulation, trace analysis, and qualitative inquiry? **Test 5 - Cumulative stability.** Can the theory accumulate across technologies, tasks, cultures, and historical periods without repeatedly redefining its basic objects? The present assessment is: ----------------------------------------------------------------------- **Test** **Current result** **Basis** ----------------------- ----------------------- ----------------------- Domain coherence Partly satisfied Human-computational interaction can be defined as temporally extended reciprocal causal coupling, independent of a named product. Conceptual Not satisfied Every candidate core irreducibility concept has close counterparts in one or more established fields. Predictive increment Not demonstrated No cross-domain benchmark shows that interaction-specific constructs outperform a principled integration of existing models. Methodological Not satisfied The required methods necessity already exist, although their integration and reporting standards are uneven. Cumulative stability Not yet demonstrated HCI contains enduring laws and models, but the field\'s use of \"interaction\" remains conceptually diverse and often underspecified. ----------------------------------------------------------------------- The negative conclusion follows mainly from Tests 2 and 3. A coherent domain is not sufficient for a new discipline if its explanatory mechanisms are already available and no incremental success has been shown. ## 1.2 Existing labels do not establish an autonomous discipline A nominal precedent exists: the *Journal of Interaction Science* began in 2013, and its revised scope described Interaction Science as a deliberately broad, transdisciplinary umbrella spanning biological and technical parties, multiple methods, and socio-technical design (Bahr & Stary, 2016). This demonstrates an institutional program, not conceptual irreducibility. Its definition depends explicitly on integrating psychological, social, engineering, and design traditions. The same pattern appears inside HCI. HCI has been described as a science, an inter-discipline, and a field with multiple concepts of interaction rather than a single stable theoretical core (Blackwell, 2015; Reeves, 2015; Hornbæk & Oulasvirta, 2017; Hornbæk et al., 2019). A 2025 synthesis treats theories of interaction - information and control, dialogue, tool use, automation, rationality, and practice - as a core part of HCI rather than as a separate discipline (Hornbæk, Kristensson, & Oulasvirta, 2025). Computational interaction and computational rationality likewise present formal explanatory programs within HCI (Oulasvirta et al., 2018; Oulasvirta, Jokinen, & Howes, 2022). A field label therefore exists in a weak sociological sense, but no reviewed program establishes the stronger scientific claim required here: a stable, non-redundant ontology and mechanism set that cannot be housed in existing disciplines. # 2. Scope and core explanandum ## 2.1 Scope The scope is **human interaction with computational processes**, not the design of any particular interface and not every relation between humans and technology. A computational process may be deterministic, probabilistic, adaptive, distributed, autonomous, embedded, or materially embodied. The theory must survive replacement of current devices, software platforms, visual conventions, and organizations. This scope includes: - moment-to-moment perception-action coupling; - human and computational initiative, including asynchronous action; - learning, adaptation, habit, skill, and transfer across episodes; - representations and their interpretation; - physical, social, organizational, linguistic, and cultural mediation; - breakdown, ambiguity, negotiation, and repair; - individual and collective activity when computational artifacts participate in the cognitive or organizational system. It excludes, unless linked to reciprocal coupling: - one-way exposure to static information; - general cognition with no computational process in the causal loop; - product evaluation whose claims do not generalize beyond the implementation; - normative design recommendations presented as explanations. ## 2.2 Working definition of interaction **Human-computational interaction** is a temporally extended reciprocal causal coupling in which human action or state conditions subsequent computational states or actions, and computational action or state conditions subsequent human observations, action opportunities, actions, or learned state. Reciprocal does not mean equal, synchronous, conversational, or beneficial. Coupling may be intermittent, delayed, opaque, probabilistic, socially mediated, or distributed across people and artifacts. A single event such as a click is not by itself an interaction; it is one observation within a trajectory whose meaning depends on prior state, alternatives, consequences, and interpretation. ## 2.3 Explanatory target A general theory should explain or predict the distribution of interaction trajectories and outcomes given: - the current joint human-computational-environmental state; - goals, tasks, motives, and institutional objects; - what actions are feasible, signaled, and believed possible; - the representations through which state and action possibilities are made available; - human capabilities, beliefs, skills, expectations, and prior learning; - computational transition and action policies; - physical, social, cultural, linguistic, and organizational context; - feedback, latency, uncertainty, and consequences. This is a coherent target. The literature review below asks whether it is already decomposed by established disciplines. # 3. Method and evidential basis This report is a boundary review and conceptual synthesis, not a claim of exhaustive bibliometric coverage. It combines the uploaded foundational corpus with selected primary and canonical literature chosen to test the proposed explanatory boundaries. The uploaded corpus covers ecological perception, cognitive engineering, situated action, distributed cognition, activity theory, interaction design, everyday design, and computational modeling. It was assessed under the accompanying research canon: concepts must arise from necessity, remain implementation-independent, distinguish observation from inference, be measurable in principle, be falsifiable, and add to a shared ontology rather than duplicate vocabulary. Two source limitations were handled explicitly. The uploaded file titled *Cognition in the Wild* is a review rather than the complete book, so claims about distributed cognition were checked against Hutchins\'s primary formulations and the later distributed-cognition program in HCI. The uploaded Engeström file is a critical essay about activity theory, so the review distinguishes Engeström\'s primary framework from that critique (Blunden, 2015). The analysis proceeds in four stages: 6. identify what each adjacent field treats as its explanatory unit and mechanism; 7. identify where each field stops or becomes weak; 8. map the proposed candidate concepts onto established terminology; 9. retain only residual additions that support discriminating empirical tests. # 4. Literature review and explanatory boundaries ## 4.1 Boundary matrix --------------------------------------------------------------------------- **Discipline or **Primary contribution, **Boundary, overlap, and program** assumptions, and residual gap** strengths** ----------------------- ----------------------- --------------------------- **Human-Computer Studies the design, HCI already contains most Interaction** use, and consequences of the proposed domain. Its of interactive weakness is not absence of computing. It coverage but theoretical contributes pluralism: \"interaction\" experimental methods, is used as dialogue, field methods, design transmission, tool use, research, usability and embodiment, optimal experience constructs, behavior, and other interaction techniques, concepts. HCI frequently and a large body of mixes explanation, models. Its strength is evaluation, and direct engagement with prescription. The residual computational artifacts gap is a shared, testable and the diversity of integration across settings in which they paradigms and time scales, are used (Hornbæk & not a new subject matter. Oulasvirta, 2017; Hornbæk et al., 2019; Hornbæk, Kristensson, & Oulasvirta, 2025). **Cognitive engineering Card, Moran, and Newell It is deliberately narrow: and classical developed the Model expert performance, quantitative HCI** Human Processor, GOMS, temporal prediction, and the keystroke-level tasks that can be model, unit-task decomposed reliably. It analysis, and explicit handles neither open-ended links between cognitive interpretation nor theory and engineering institutional and cultural prediction. The organization well. Its approach assumes \"operators\" are useful decomposable goals, model-relative units, not operators, methods, universal interaction selection rules, and primitives. bounded processing stages. It is strongest for practiced, routine, measurable tasks (Card et al., 1983; Newell & Card, 1985). **Human factors and Explains performance It can understate meaning, cognitive systems and safety in work identity, culture, and engineering** systems through everyday appropriation when workload, attention, performance and control control, automation, dominate the analysis. error, situation Cognitive work analysis and awareness, joint cognitive systems skill-rule-knowledge already cover many proposed modes, and joint context and system cognitive systems. It concepts. The residual assumes that human and problem is linking technical components operational models to should be analyzed as semantic and longitudinal an operational system learning accounts without under constraints. It reducing either. is strong for high-consequence, time-critical, and adaptive work (Rasmussen, 1983; Vicente, 1999; Parasuraman et al., 2000; Hollnagel & Woods, 2005). **Cognitive Provides experimentally Laboratory tasks and psychology** grounded mechanisms for individual-level models can perception, attention, neglect distributed memory, decision, resources, social problem solving, skill organization, historical acquisition, practice, and institutional automaticity, mental constraints. Still, models, and transfer. accumulated experience, It assumes behavior can strategy change, learning be explained through curves, mental models, and measurable cognitive transfer are established processes and topics; they do not require representations, new umbrella terms. although schools disagree about their form (Norman, 1983; Logan, 1988; Singley & Anderson, 1989). **Cognitive science** Integrates psychology, It is broader than neuroscience, interaction and may not linguistics, prioritize the special philosophy, artificial causal role of intelligence, and computational artifacts. computational modeling. However, its frameworks It supplies already express latent representational, state, partial embodied, Bayesian, observability, learning, dynamical, and action selection, and resource-rational representation. The accounts of cognition. residual gap is Its strength is domain-specific integration mechanistic plurality and validation, not missing and formal model formal machinery. comparison (Chemero, 2009; Gershman et al., 2015; Farrell & Lewandowsky, 2018). **Ecological Gibson treats Strong direct-perception psychology** perception and action claims remain contested, as relations between an and the framework is less organism and a complete for conventional structured environment. symbols, propositional Affordances are meaning, hidden agent-environment computational states, and relations, and institutional rules. It perceptual information supplies a necessary can specify action relational correction but possibilities without not a complete theory of requiring a computational interaction. reconstruction of the physical world. It is strong for embodiment, real-time coupling, and the relational nature of action possibilities (Gibson, 1979; Chemero, 2009). **Situated action, Suchman shows that They provide exceptional ethnomethodology, and plans are resources for sensitivity to context and conversation analysis** situated action rather the underdetermination of than complete intention by observable determinants of behavior. They are less conduct. oriented toward Ethnomethodology and cross-domain quantitative conversation analysis prediction and formal explain how learning models. Their intelligibility, major implication is sequencing, common methodological: event logs ground, trouble, and do not reveal meaning repair are locally without the circumstances produced. These and practices that make approaches assume actions intelligible. action is indexical and accountable within unfolding circumstances (Sacks et al., 1974; Clark & Brennan, 1991; Suchman, 1987). **Distributed Hutchins and later HCI The analyst must choose cognition** work relocate cognition system boundaries, and from an isolated accounts may understate individual to systems power, emotion, identity, of people, artifacts, or contested meaning. representations, and Distributed cognition environments. already explains why Representational states interaction cannot be propagate across media inferred from interface and time; external events alone. The residual structures transform task is to connect its computational work. It system-level descriptions is strong for teams, to measurable individual navigation, external learning and transfer. memory, workflow, and artifact-mediated reasoning (Hutchins, 1995; Zhang & Norman, 1994; Hollan et al., 2000). **Activity theory** Activity theory Its unit of analysis is explains broad, and object-oriented, operationalization and culturally mediated quantitative prediction are activity through difficult. Engeström\'s subjects, tools, activity-system diagram is community, rules, a useful heuristic but division of labor, and should not be treated as a historically developing complete social theory or a contradictions. It is micro-model of interaction. strong for collective It overlaps heavily with work, institutional proposed behavioral context context, motive, and and adaptation constructs. developmental change (Engeström, 1987; Kuutti, 1996; Kaptelinin & Nardi, 2006). **Situated cognition These programs argue They vary from precise and embodied that cognition depends dynamical models to broad cognition** on bodily action, philosophical positions. environmental Their concepts can become structure, and task too general unless tied to context rather than explicit observables. They only internal symbol reinforce the need for manipulation. They joint-state and environment explain offloading, variables but do not sensorimotor uniquely define a science regularities, and the of interaction. role of material arrangements (Lave & Wenger, 1991; Dourish, 2001; Chemero, 2009). **Learning sciences and Skill acquisition, Transfer is often difficult skill-transfer instance learning, to predict because research** proceduralization, similarity is transfer of training, multidimensional and situated learning, representation-dependent. apprenticeship, and This is a genuine empirical communities of practice gap, but the constructs explain how experience already exist. The needed changes future addition is a typed performance. Transfer similarity and equivalence research connects schema plus stronger source and target tasks longitudinal designs. through shared components, productions, principles, or participation structures (Logan, 1988; Singley & Anderson, 1989; Lave & Wenger, 1991). **Information Studies how visual Its domain is narrower than visualization and encodings, spatial interaction as a whole and graphical perception** organization, often assumes a defined perceptual tasks, and analytic task. It already external explains why visual representations affect structure can affect action accuracy, search, before full task inference, and interpretation, but it does reasoning. It not support a simple establishes that visual-versus-semantic informationally serial pipeline. equivalent displays may impose different computational costs and that elementary visual judgments differ in precision (Cleveland & McGill, 1984; Larkin & Simon, 1987). **Information Explains organization, Information architecture is architecture and human labeling, navigation, often prescriptive and information search, findability, practice-oriented rather interaction** information behavior, than a general causal and the relation science. Human information between information interaction is broader and practices and systems. ecological but focuses on It assumes that people relations with information act within structured rather than all information computational action. These environments and use fields cover much of multiple strategies to semantic organization and seek, avoid, assess, wayfinding without and organize requiring new terminology. information (Pirolli & Card, 1999; Fidel, 2012; Rosenfeld et al., 2015). **Semiotics and Distinguishes signs, Semiotic analysis is often semiotic engineering** objects, interpretants, interpretive and may lack codes, and discriminating quantitative meaning-making. predictions. Meaning is not Semiotic engineering exhausted by designer treats an interface as communication, especially a medium through which in adaptive, appropriated, designers communicate a or multi-agent systems. It model of intended use nevertheless makes a new to users. It is strong \"semantic representation\" for the distinction construct unnecessary between representation unless the proposed term is and meaning and for more precise. failures of interpretation (de Souza, 2005). **Systems theory, Supplies feedback, Generic systems language cybernetics, and state, transition, can become vacuous unless control** regulation, stability, variables and mechanisms adaptation, are domain-specific. observability, and Classical control is often requisite variety. It thin on interpretation, treats behavior as social meaning, and trajectories of coupled learning. The residual systems rather than challenge is not feedback isolated events. This itself but integration with is the clearest cognition, representation, existing formal basis and culture. for reciprocal interaction (Wiener, 1948; Ashby, 1956; von Bertalanffy, 1968). **Dynamical systems and Explains temporally Complexity vocabulary is complexity science** extended, nonlinear, easy to use metaphorically emergent, and does not identify the path-dependent, and correct state variables by multi-scale behavior. itself. It contributes It supports analysis of methods and cautions, but attractors, no distinctive interaction coordination, phase ontology follows merely transitions, and from calling interaction development without complex. assuming fixed symbolic programs (Simon, 1962; Thelen & Smith, 1994). **Anthropology and Provides thick Generalization is analytic ethnography** description of rather than usually practice, culture, law-like, and comparative meaning, materiality, measurement can be identity, institutions, difficult. Anthropology and local categories. already supplies the Ethnographic work in antidote to demographic HCI reveals how determinism and technologies are context-free appropriated and how interpretation. The formal system residual task is principled descriptions diverge translation between local from actual practice explanations and (Geertz, 1973; Suchman, cross-setting models. 1987; Dourish, 2001). **Behavioral economics Models bounded choice, Choice models cover only and decision science** reference dependence, part of interaction and can heuristics, framing, ignore perception-action uncertainty, learning, dynamics, social practice, incentives, and choice and meaning. Still, they architecture. Its make \"behavior relative to central strength is available actions\" an explicit comparison established idea. Any between available interaction model should alternatives, beliefs, distinguish objective, utilities, and observed signaled, and believed choices (Simon, 1955; choice sets. Kahneman & Tversky, 1979). **Interaction design Produces artifacts, Design knowledge is not and design research** methods, experiential automatically explanatory. accounts, and A successful artifact prescriptive knowledge demonstrates possibility, about how interactions not a general mechanism. might be configured. It Interaction design should is strong at generating remain a major source of possibilities, hypotheses and discovering interventions, while requirements, and descriptive theory and exposing phenomena prescription remain through making (Rogers explicitly separate. et al., 2011; Norman, 2013). **Computational Uses formal models, Existing models often interaction and optimization, concentrate on tasks with computational cognitive simulation, tractable objectives and modeling** probabilistic measurable performance, and inference, they remain weaker on reinforcement learning, social institutions, and model comparison to contested meaning, explain behavior and identity, and historical improve interactive practice. This program is systems. the closest existing Resource-rational and vehicle for the proposed bounded-agent formal science; creating a approaches connect separate discipline before environmental extending it would be structure, human premature. limitations, and adaptive policy (Oulasvirta et al., 2018; Oulasvirta, Jokinen, & Howes, 2022). --------------------------------------------------------------------------- ## 4.2 What the literature collectively explains Taken together, the adjacent fields already explain the main phenomena in the working direction: - **Experience affects later behavior** through learning, memory, mental models, procedural skill, automaticity, habit, and transfer. - **Current events underdetermine meaning** because observable action admits multiple intentions and because cognition may be distributed across people, artifacts, and circumstances. - **Behavior is conditional on alternatives and constraints** through affordances, choice sets, bounded rationality, task analysis, and control. - **Representation and meaning are distinguishable** through semiotics, distributed representations, graphical perception, and external cognition. - **Visual structure changes behavior** through perceptual organization, search, encoding accuracy, spatial indexing, and computational cost. - **Interaction has formal structure** through feedback loops, state-transition systems, GOMS operators, control models, conversation sequences, and activity hierarchies. - **Context is constitutive rather than decorative** through situated action, anthropology, activity theory, ecological psychology, and distributed cognition. - **Social organization changes cognition and action** through common ground, division of labor, rules, roles, and institutional objects. No candidate phenomenon is presently an unexplained residue shared by no existing field. ## 4.3 Where the literature collectively stops The literature is weaker at four integrations. ### 4.3.1 Cross-timescale integration Momentary perception and action, episode-level strategy, long-term learning, and historical or institutional change are usually modeled separately. A theory needs explicit mappings between them. Prior history should influence present action through identifiable current states - beliefs, skill, expectations, habits, social position, or access - rather than through an unanalyzed history variable. ### 4.3.2 Typed representation equivalence Research shows that the same information can be represented in behaviorally different ways, but studies often use \"equivalent\" without specifying the relation. Semantic equivalence, informational equivalence, task equivalence, computational equivalence, and interactional equivalence are not interchangeable. ### 4.3.3 Context-conditioned behavioral evidence Event traces are routinely analyzed without a sufficient record of what the person could perceive, what actions were feasible, what actions were signaled, what the person believed possible, or what social constraints applied. This makes intention and strategy weakly identifiable (Dey, 2001; Suchman, 1987). ### 4.3.4 Cross-scale predictive comparison Contextual and social theories often explain cases richly but do not compete in shared predictive benchmarks. Formal models often predict constrained tasks but omit social and historical variables. There is no standard benchmark that tests whether adding those variables improves held-out prediction across implementations. These are integration and evaluation gaps. They do not yet establish a new discipline. # 5. Critique of the current working direction ## 5.1 \"Interaction behavior develops through accumulated experience interacting with information systems\" **Disposition: established but underspecified.** Skill acquisition, instance learning, procedural knowledge, mental models, transfer, and situated learning already cover this claim (Norman, 1983; Logan, 1988; Singley & Anderson, 1989; Lave & Wenger, 1991). \"Accumulated interaction experience\" is too broad to function as a mechanism. Two people can have equal exposure counts but different learned states because the experiences differed in feedback, goals, attention, success, spacing, social support, and interpretation. The stronger formulation is: Prior interaction episodes affect future behavior only insofar as they change currently operative states or environments, such as beliefs, skills, expectations, habits, perceived action possibilities, social roles, or access to external resources. This formulation is falsifiable. If history has no residual effect after those mediators are measured adequately, a separate history construct is unnecessary. If a residual persists, the scientific task is to identify the missing mediator rather than preserve history as an opaque cause. ## 5.2 \"Previous interaction experiences influence future interaction\" **Disposition: true but nearly tautological without conditions.** The proposition needs a defined source experience, target interaction, causal contrast, mechanism, direction, and time interval (Singley & Anderson, 1989). Experience can improve, impair, or leave target performance unchanged. Familiar cues can produce negative transfer when mappings reverse. Forgetting, interference, and contextual specificity constrain persistence. Use the established term **transfer of learning** or **transfer of skill**. Define it counterfactually as the change in target behavior caused by prior source experience under otherwise comparable target conditions. ## 5.3 \"Interaction cannot be fully understood from interface events alone\" **Disposition: generally correct, but \"fully\" is untestable and the boundary is task-dependent.** Situated action, distributed cognition, ethnomethodology, and cognitive modeling all show that the same observable event can arise from different intentions, strategies, beliefs, or circumstances (Card et al., 1983; Suchman, 1987; Hollan et al., 2000). However, event-only models can be adequate for narrow prediction problems such as practiced pointing or transcription. The defensible claim is: An event trace is insufficient for any inference whose competing mechanisms predict the same event distribution under the recorded variables. This turns a slogan into an identifiability criterion. More context is required only when it discriminates among plausible explanations or supports the target intervention. ## 5.4 \"Behavior should be interpreted relative to the information, actions, and constraints available at the time\" **Disposition: strongly supported, with one necessary refinement.** Affordance, signifier, bounded-choice, and control traditions all require action to be interpreted against opportunities and constraints (Simon, 1955; Gibson, 1979; Norman, 2013). \"Available\" must be split into at least three sets: - **feasible action set:** actions physically and computationally permitted; - **signaled action set:** actions made perceptually discoverable by the current representation; - **believed action set:** actions the person represents as possible. These sets can differ. A function may be feasible but not signaled; signaled but not understood; believed possible but unavailable; or socially prohibited despite technical feasibility. Behavior should be interpreted against the relevant set for the proposed mechanism. ## 5.5 \"Semantic understanding may exist independently of visual representation\" **Disposition: reject the strong independence claim; retain the distinction.** Meaning and visual form are analytically distinct, and the same content can be expressed through visual, auditory, tactile, linguistic, or procedural representations (Zhang & Norman, 1994; de Souza, 2005). But human semantic understanding is always mediated by some perceptible or remembered representation and by prior knowledge. It is therefore misleading to say that meaning exists independently of representation in the psychological process. Use three terms: - **representation:** a perceptible or manipulable form that can carry distinctions; - **content:** what a representation is taken to be about under a code or practice; - **interpretation:** an agent\'s situated mapping from representation to believed content, implication, or action. This separation preserves the intended insight without treating meaning as a free-standing object. ## 5.6 \"Visual structure may influence interaction before semantic understanding is fully formed\" **Disposition: plausible and partly supported, but not as a universal serial stage.** Graphical perception and attention research show that some visual features and spatial relations influence detection, search, and action rapidly (Treisman & Gelade, 1980; Cleveland & McGill, 1984; Larkin & Simon, 1987). Larkin and Simon show that informationally equivalent diagrams can reduce search and inference costs. Yet semantic expectations can also guide early attention, and expertise changes what structure is perceived. The testable version is: Under specified exposure, task, and expertise conditions, differences in visual encoding produce early differences in attention or action that remain after semantic content is held constant. This is an empirical hypothesis about timing and mediation, not a foundational axiom. ## 5.7 \"Interaction may be describable through a stable set of primitives independent of specific software\" **Disposition: unproven and likely false if \"primitive\" means universal cognitive atom.** Existing traditions propose different units because they answer different questions (Sacks et al., 1974; Card et al., 1983; Kuutti, 1996): keystrokes and mental operators in GOMS, perception-action cycles in ecological psychology, turns and repair sequences in conversation analysis, actions and operations in activity theory, and state transitions in control models. No context-free smallest meaningful unit has been established. The minimum defensible instrumentation unit is a **closed-loop transition record**: prior state and opportunities, one or more agent actions, resulting transition, and observable consequence. This is a data schema, not a claim that cognition is composed of such atoms. # 6. Recommended terminology ## 6.1 Candidate-term disposition ----------------------------------------------------------------------- **Candidate term** **Recommendation** **Reason** ----------------------- ----------------------- ----------------------- Accumulated interaction Replace with Exposure is not a experience **interaction history** mechanism; current for records and beliefs, skills, **learned state** for expectations, habits, mechanisms and social position mediate effects. Visual structure Use **visual Established terms are encoding**, more specific and **perceptual measurable. organization**, or **spatial layout** as appropriate Interaction primitives Use **model-relative The correct grain operators** or depends on the **state-transition explanandum. roles**; reject a universal primitive claim Semantic representation Split into Prevents form, meaning, **representation**, and agent understanding **content**, and from being conflated. **interpretation** Behavioral context Use **task, \"Context\" is environmental, social, otherwise an unbounded and institutional residual category. context**, explicitly enumerated Interaction strategies Use **strategy**, These terms have **policy**, or distinct formal **method** and state meanings. which theory is intended Adaptation and learning Retain established Different time scales terms; distinguish and mechanisms should within-episode not be collapsed. adaptation, learning, development, and system adaptation Behavioral evidence Use **behavioral Data are not evidence trace** for observation for a claim until and **evidence under an linked through a observation model** for validity argument. inference Interaction measurement Retain as a Measurement concerns methodological area, many constructs and not a construct does not define a new object. Interaction modeling Retain as a research The phrase alone states activity; specify no theory. cognitive, control, statistical, social, or computational model Representation Replace with **typed Equivalence must equivalence equivalence relation** specify semantic, informational, task, computational, or interactional criteria. Interaction similarity Use a **similarity Surface, semantic, profile** over declared operational, temporal, dimensions, not a and social similarity single scalar by can diverge. default Interaction transfer Use **transfer of The phenomenon is learning** or established; the domain **transfer of skill in qualifier is human-computational sufficient. interaction** ----------------------------------------------------------------------- ## 6.2 Terms that should not be introduced Do not coin new terms for mental models, affordances, feedback, constraints, strategy, transfer, skill, external representation, common ground, repair, context, or distributed cognition unless an empirical result demonstrates that the established construct cannot express the required distinction. # 7. Canonical ontology The ontology below is intentionally small. It is not a claim that every theory must use every entity. It is a shared translation layer that permits theories to state which entities they include, omit, or redefine. ## 7.1 Entities and relations ------------------------------------------------------------------------------------------------- **Concept** **Canonical definition** **Typical **Status** operationalization** -------------------- ----------------------------------- ---------------------- ----------------- **Human agent** A person or coordinated human group Participant identity, Established. whose actions and learned states role, capabilities, participate in the interaction group membership, trajectory. coordination structure. **Computational A rule-governed, stateful process State machine, Established. process** that transforms information or acts probabilistic policy, in an environment and can condition service, algorithm, later human observations or controller, model, or opportunities. distributed process. **Environment** Physical, informational, social, Device setting, Established. and institutional conditions not location, surrounding assigned to the focal agents but artifacts, norms, causally relevant to the organization, other trajectory. actors, environmental disturbances. **Joint state** The external state of the coupled Synchronized system Synthesis of human-computational-environmental state, artifact state, systems concepts. system at a specified time and task state, location, grain. active roles, resource availability. **Goal** A represented desired condition Instruction, stated Established. that guides action selection. goal, inferred subgoal, reward structure. **Task** A normative or analytic Task protocol, work Established. specification of conditions, demand, benchmark. transformations, and completion criteria. **Object or motive** The socially or historically Work objective, Established in meaningful object toward which institutional purpose, activity theory; collective activity is organized. community practice. not reducible to an immediate goal. **Representation** A perceptible or manipulable form Text, sound, spatial Established. that preserves distinctions and can arrangement, haptic support interpretation or action. pattern, physical artifact, state display, conversational utterance. **Content** What a representation is taken to Proposition, referent, Established. concern under a code, convention, data relation, domain or practice. state. **Interpretation** An agent-relative mapping from Comprehension Established representation and context to response, prediction, synthesis. believed content, implication, or explanation, action relevance. categorization, action choice, model-based latent variable. **Observation** Information available to an agent Rendered display, Established. about joint state through current sound, haptic channels. feedback, system message, remembered or externally stored cue. **Feasible action Actions permitted by current Enumerated commands, Established set** physical, computational, and formal enabled controls, choice/control constraints. reachable states, API concept. permissions. **Signaled action Feasible or infeasible actions made Visible controls, Synthesis of set** perceptually discoverable by the prompts, signifiers, signifier and representation. menu entries, action-set affordance cues. concepts. **Believed action Actions the human agent currently Elicitation, Established set** represents as possible or relevant. prediction from belief/choice behavior, recognition concept. test, mental-model probe. **Constraint** A relation that removes, penalizes, Physical lockout, Established. delays, or socially prohibits validation rule, time possible states or actions. pressure, policy, norm, cost, capability limit. **Action** An intervention by an agent that Motor action, command, Established. can change joint state or the utterance, delegation, information available to another system-initiated agent. operation. **Transition** A change in joint state generated Logged state change, Established. by prior state, agent actions, and computational disturbances. transition, physical consequence. **Feedback** An observation whose value depends Confirmation, error, Established causally on a prior action or state movement, latency cybernetic and can regulate subsequent action. signal, consequence, concept. social response. **Outcome** A state or measure used to evaluate Completion, error, Established. an episode relative to a task, time, utility, safety, goal, value, or analytic question. learning, coordination quality. **Strategy or A mapping, explicit or implicit, Sequence model, verbal Established. policy** from represented state and goals to protocol, policy action selection over time. parameters, GOMS method, inferred latent strategy. **Learned state** Relatively persistent agent state Beliefs, mental model, Established changed by experience and capable procedural knowledge, umbrella for of affecting later interpretation skill parameters, model or action. habits, expectations, integration. learned policy. **Interaction A temporally ordered record of Longitudinal trace, Descriptive history** prior episodes and consequences, exposure record, record, not whether or not retained by the training history. mechanism. agent. **Episode** An analytically bounded segment of Task trial, Necessary a trajectory selected by a declared conversational analytic criterion. sequence, work shift, convention; not a session, project natural atom. phase. **Breakdown and A failure of expected coordination Error recovery, Established. repair** or intelligibility and the actions clarification through which participants detect, sequence, undo, diagnose, or restore it. help-seeking, handoff repair. **Transfer** A causal change in target Matched-control Established. performance or strategy difference, attributable to prior source longitudinal experience. crossover, retention and generalization tests. **Behavioral trace** A time-ordered record of observable Event log, video, Observation. actions and states produced during motion trace, an episode. conversational transcript. **Observation An explicit account of how latent Measurement model, Established model** constructs and processes could coding scheme, sensor scientific generate the recorded data, model, likelihood, requirement. including omissions and error. qualitative warrant. **Evidence** Observations that discriminate Model comparison, Epistemic among claims under an explicit triangulated case relation, not raw observation model and validity evidence, intervention data. argument. effect, replication. ------------------------------------------------------------------------------------------------- ## 7.2 Typed equivalence relations A single relation called \"representation equivalence\" is too coarse. Use the following types. ----------------------------------------------------------------------- **Type** **Definition** **Example consequence** ----------------------- ----------------------- ----------------------- **Syntactic Same tokens or Useful for equivalence** structural encoding implementation under a declared comparison; says little grammar. about meaning or use. **Informational The same task-relevant Two displays may be equivalence** information can in informationally principle be recovered. equivalent yet impose different search and inference costs. **Semantic The representations Does not imply equal equivalence** express the same discoverability or referent, proposition, performance. or domain relation under a declared interpretive scheme. **Task equivalence** The same goal and Does not imply the same success conditions action sequence or apply. cognitive demands. **Computational The same Stronger than equivalence** transformations can be informational completed with equivalence and comparable resource model-dependent. requirements under a declared model. **Interactional Two conditions yield Empirical and equivalence** equivalent explicitly population-, distributions of context-, and strategies, actions, metric-bound. outcomes, or learning for a specified population and context within a tolerance. ----------------------------------------------------------------------- Equivalence in one type does not entail equivalence in another. The distinction directly explains why semantically identical controls can behave differently, why visually different systems can support transfer, and why surface similarity can create negative transfer. ## 7.3 Interaction similarity profile Interaction similarity should normally be represented as a vector rather than a single score. Candidate dimensions are: - goal and task structure; - semantic relations; - state-transition topology; - action-effect mappings; - required perceptual discriminations; - required cognitive operations or productions; - feedback timing and reliability; - physical or motor demands; - error and repair structure; - social roles, norms, and division of labor; - representation conventions; - reward, risk, and institutional consequences. A scalar similarity measure is justified only after a model shows how dimensions combine for the target prediction. # 8. Foundational assumptions These assumptions define the proposed integration program. They are not asserted as universal truths beyond its scope. 10. **Reciprocal coupling:** interaction requires a causal loop, although influence can be delayed, asymmetric, or mediated. 11. **Partial observability:** neither the human nor the computational process necessarily has complete access to joint state, intentions, or consequences. 12. **Bounded agency:** action is constrained by perception, cognition, embodiment, time, resources, permissions, and social organization. 13. **Historical mediation:** prior episodes matter through changed learned state, external resources, relationships, or institutions. 14. **Representational mediation:** computational state affects human action through representations and channels, and human action affects computation through encodings and sensors. 15. **Interpretive variability:** the same representation can support different interpretations across people, times, and practices. 16. **Multiple time scales:** perception-action coupling, strategy, learning, development, organizational change, and cultural change may obey different dynamics. 17. **Context specificity:** explanatory relevance is claim-dependent; context must be enumerated rather than treated as an unlimited background. 18. **Social causation:** norms, roles, language, power, access, and institutions can be causal components, not merely demographic descriptors. 19. **Implementation independence:** core claims refer to relations and mechanisms, not named technologies or interface conventions. 20. **Measurement dependence:** latent constructs are not directly observed; every inference depends on an observation model and validity evidence. 21. **Heterogeneity:** population averages do not automatically describe individual mechanisms or subgroup distributions. # 9. First principles 22. **Interaction is a trajectory, not an isolated event.** Events acquire explanatory meaning through prior state, alternatives, consequences, and subsequent adaptation. 23. **Behavior must be conditioned on opportunities.** An action cannot be interpreted without distinguishing what was feasible, signaled, believed possible, and socially permitted. 24. **History is not a mechanism.** Prior experience should be decomposed into the states and external structures through which it affects present behavior. 25. **Representation is not meaning.** Form, content, and situated interpretation are distinct, even though human meaning is always representationally mediated. 26. **Equivalence is typed.** No claim of sameness is complete without a declared relation, population, context, metric, and tolerance. 27. **Primitives are model-relative.** The smallest useful unit is determined by the explanatory question; no universal cognitive atom should be presumed. 28. **Context is bounded by contrast.** Include a contextual variable when it changes a prediction, intervention, or interpretation among plausible alternatives. 29. **Social categories are not default mechanisms.** Demographic variables require causal pathways, measurement invariance, and attention to within-group heterogeneity. 30. **Explanation precedes prescription.** A design recommendation is not evidence that the proposed mechanism is correct. 31. **New constructs require incremental success.** A term earns canonical status only when it explains or predicts something that established constructs cannot with equal parsimony. # 10. Relationships among concepts ## 10.1 Core causal cycle At a declared time scale, goals, learned state, and context shape an agent\'s interpretation of observations. Interpretation and believed action possibilities shape strategy and action. Human and computational actions jointly produce a state transition. The new state is represented through perceptual channels as feedback. Feedback and outcome update learned state and may modify the external environment, social relations, or computational policy. Repeated transitions form an episode; repeated episodes create an interaction history. ## 10.2 Dependency graph ![Figure 1. Dependency graph for the minimum ontology. Arrows indicate explanatory dependence, not necessarily temporal precedence.](media/image1.png "Minimum interaction ontology dependency graph"){width="6.65in" height="5.006936789151356in"} Figure 1. Dependency graph for the minimum ontology. Arrows indicate explanatory dependence, not necessarily temporal precedence. The graph has two important asymmetries. First, interaction history is upstream of current behavior only through learned state or changed external conditions. Second, behavioral traces become evidence only through an observation model and an explicit claim; a trace is not self-interpreting. # 11. Minimum formal model A useful integration model should be general enough to compare theories but constrained enough to generate discriminating predictions. The following is a template, not a claim that humans literally implement a particular control or reinforcement-learning algorithm. Let: - [x_t]{.mark} be joint external state at time [t]{.mark}; - [z_t]{.mark} be the human learned state, including beliefs, skill, expectations, and strategy parameters; - [q_t]{.mark} be task, social, and institutional context; - [r_t]{.mark} be the representation generated from current state; - [F_t]{.mark}, [S_t]{.mark}, and [B_t]{.mark} be feasible, signaled, and believed human action sets; - [h_t]{.mark} be human action; - [c_t]{.mark} be computational action, including autonomous or delayed action; - [o_t]{.mark} be the human observation produced through representation and environment; - [y_t]{.mark} be an outcome measure. A minimal coupled process is: [r_t = R(x_t, q_t)]{.mark} [o_t \~ O_H(r_t, x_t, q_t)]{.mark} [B_t \~ I(o_t, z_t, q_t)]{.mark} [h_t \~ pi_H(h \| o_t, B_t, z_t, q_t, goal_t)]{.mark} [c_t \~ pi_C(c \| x_t, h\_\<=t, q_t)]{.mark} [x\_(t+1) \~ T(x_t, h_t, c_t, q_t, disturbance_t)]{.mark} [y_t = Y(x_t, h_t, c_t, x\_(t+1), q_t)]{.mark} [z\_(t+1) \~ U(z_t, o_t, h_t, c_t, y_t, q_t)]{.mark} This template makes several empirical questions explicit: - Does the representation change behavior through observation, interpretation, or both? - Does prior history add predictive value after [z_t]{.mark} is measured? - Do social or institutional variables change the policy, transition, or outcome function? - Are two representations equivalent under [R]{.mark}, [I]{.mark}, the policy, or only the outcome metric? - Does a theory predict held-out trajectories when the implementation changes but the declared structure remains constant? ## 11.1 Why this is not a new theory by itself Every component has precedents in control theory, partially observed decision processes, cognitive modeling, ecological action, distributed cognition, and HCI. Its contribution is a common interface among theories. Scientific value arises only if specific submodels generate risky predictions and outperform alternatives. # 12. Smallest meaningful unit of interaction There is no theory-independent smallest meaningful unit. - For keystroke-level timing, an operator can be useful. - For conversational intelligibility, a turn, adjacency pair, or repair sequence may be minimal. - For ecological control, a perception-action cycle or continuously coupled variable is more appropriate. - For activity theory, an operation has meaning only within an action, and an action only within an activity. - For distributed cognition, the relevant unit may span people and artifacts. The recommended minimum **recording unit** is a closed-loop transition: [\]{.mark} It is the smallest record that can support a causal interaction claim without treating an input event as self-explanatory. It is not asserted to be the smallest psychological or social unit. # 13. What constitutes evidence in interaction research ## 13.1 Observation is not evidence by itself A click, utterance, error, gaze fixation, or completion time is an observation. It becomes evidence for a claim only when: - the construct and competing explanations are specified; - the observation process and missing data are understood; - the relevant alternatives and constraints are recorded or experimentally controlled; - the measure has a validity argument; - the analysis discriminates among models or causal contrasts; - uncertainty and heterogeneity are reported. ## 13.2 Context-complete interaction record A reusable empirical record should contain, when relevant: ----------------------------------------------------------------------- **Component** **Minimum content** ----------------------------------- ----------------------------------- Provenance Clock, episode, participant or role, device/channel, data version, synchronization uncertainty. Pre-state Computational state, task state, active representation, environmental and social state. Opportunity structure Feasible, signaled, and, when measured, believed action sets; permissions and constraints. Action Actor, action type, parameters, onset, duration, confidence or coding uncertainty. Transition Resulting state change, latency, system initiative, stochasticity, external disturbances. Feedback What became perceptually available to each agent and when. Outcome Task, safety, utility, learning, coordination, or experiential measure with declared validity. History Relevant prior exposures, training, expertise, recent episodes, and external resources. Context Goal, motive, language, role, norms, organization, location, stakes, collaboration. Interpretation evidence Comprehension, prediction, explanation, recall, self-report, or qualitative account, kept distinct from behavior. ----------------------------------------------------------------------- Not every study needs every field. The rule is contrastive: retain the variables required to distinguish the mechanisms under test. ## 13.3 Evidence hierarchy by claim type There is no universal hierarchy in which laboratory experiments always outrank field evidence. Appropriate evidence depends on the claim. - **Causal effect of a representation:** randomized or strongly identified intervention, with manipulation checks and process measures. - **Mechanism of skilled action:** quantitative model comparison, perturbation, and out-of-sample prediction. - **Meaning and local intelligibility:** interaction analysis, ethnography, conversation analysis, and participant accounts tied to recorded conduct. - **Longitudinal learning and transfer:** repeated measures, retention, matched controls, cross-system target tasks, and mediation analysis. - **Collective cognition:** synchronized traces across people and artifacts, representational-state analysis, and field validation. - **Institutional or cultural effects:** comparative and multilevel designs, measurement invariance, process evidence, and explicit treatment of power and access. Triangulation is valuable when methods test different links in the same causal or interpretive argument, not merely when many data types are collected. # 14. Universals, acquisitions, and population variation ## 14.1 Plausible near-universal constraints The strongest candidates for broad generality are constraints rather than interface conventions or primitives: - finite sensory resolution, attention, memory, motor precision, and time; - dependence of control on sufficiently timely and informative feedback; - sensitivity to environmental regularities and consequences; - bodily and environmental constraints on possible action; - partial observability and uncertainty; - learning and forgetting over repeated experience; - need for coordination and repair when action is jointly organized. Even these vary quantitatively and can be altered by disability, development, tools, training, and environment. They should not be treated as fixed constants. ## 14.2 Primarily acquired components - symbolic meanings and labels; - reading direction and visual conventions; - action-effect mappings; - domain knowledge and mental models; - skilled procedures and automatic routines; - expectations imported from prior systems; - social norms, roles, and authority; - language-specific categories; - occupational and institutional practices; - strategies for search, verification, recovery, and collaboration. Affordance perception often combines bodily constraints with learning. A possible action may be physically available but only discovered through cultural convention or prior experience. ## 14.3 Demographic variables Demographic categories require measurement-invariance checks and causal decomposition rather than essentialist interpretation (VanderWeele & Robinson, 2014; Sen & Wasow, 2016; Millsap, 2011). They should be handled as follows: 32. **Describe sampling and inequity.** Age, disability, gender, race, ethnicity, socioeconomic position, and geography may be necessary to assess who is represented and who bears costs. 33. **Do not use categories as unexplained causes.** Replace deterministic statements with mechanisms such as access, discrimination, language proficiency, literacy, education, occupational practice, exposure, motor or perceptual capability, institutional role, and trust. 34. **Recognize social causation.** Categories can have causal consequences through institutions, discrimination, segregation, norms, and resource allocation. Calling them proxies must not erase those mechanisms. 35. **Test measurement invariance.** A metric or task may not measure the same construct across languages, cultures, ages, or accessibility conditions. 36. **Model heterogeneity.** Use multilevel or distributional models, interactions specified in advance, and within-group variation rather than only group means. 37. **Avoid post hoc essentialism.** Group differences do not establish inherent traits, and absence of an average difference does not establish equal experience or equal risk. 38. **Include affected communities in construct validation.** Especially when meaning, harm, or institutional practice is part of the claim. Culture, language, education, occupation, and environment should enter models through observable practices and mechanisms where possible. They should not be reduced to fixed traits of people. # 15. Learning, adaptation, and transfer ## 15.1 Required distinctions - **Within-episode adaptation:** temporary adjustment to immediate feedback or state. - **Learning:** a retained change attributable to experience. - **Skill acquisition:** increasing reliability or efficiency in organized performance. - **Automaticity or habit:** reduced dependence on deliberative control under recurring conditions. - **Development:** longer-term reorganization of capabilities or participation. - **Transfer:** an effect of source experience on a different target condition. - **System adaptation:** change in the computational policy or representation, which can alter the human learning environment. These processes can interact but should not be collapsed. ## 15.2 Transfer definition For an outcome where higher values are better, define causal transfer as: [Transfer = E\[Y_target \| source experience\] - E\[Y_target \| matched no-source condition\]]{.mark} For time or error, reverse or standardize the direction so positive values consistently indicate improvement. The estimate must specify retention interval, target representation, target task, population, and prior knowledge. ## 15.3 Mechanistic predictions - Positive transfer should increase when source and target share required operations, causal structure, action-effect mappings, or generative principles. - Surface similarity without shared structure should produce weak transfer. - Familiar cues paired with changed consequences should produce negative transfer, especially under time pressure or automaticity. - Explicit conceptual knowledge may transfer across representations even when motor procedures do not. - Transfer should be moderated by expertise because experts encode deeper structure and novices may rely more on surface features. - System adaptation can either scaffold learning or prevent stable learning if mappings and feedback change faster than the person can form reliable expectations. These predictions are testable within existing learning and cognitive frameworks. An interaction-specific construct is warranted only if it explains residual transfer beyond them. # 16. Representation, meaning, and visual structure ## 16.1 Representation-content-interpretation triad A representation has physical or formal properties. Content is assigned under a code, convention, or practice. Interpretation is performed by an agent with a history and context. This triad prevents four common errors: - treating an icon or layout as if it contained its meaning intrinsically; - treating semantic equivalence as equal usability; - inferring interpretation directly from action without testing alternatives; - assuming that a visual redesign changes only appearance rather than computational work. ## 16.2 Visual structure Visual structure can influence interaction through at least four mechanisms: 39. **Perceptual discriminability:** some encodings support more accurate elementary judgments. 40. **Attentional guidance:** salience and spatial organization change search order and detection. 41. **Spatial indexing:** diagrams can make relevant relations co-located and reduce search. 42. **External computation:** a representation can perform part of the organizational work that would otherwise require internal transformation or memory. These effects can occur without complete semantic interpretation, but they remain task- and expertise-dependent. The appropriate experiments hold content constant, manipulate encoding, measure early process and later understanding separately, and test whether early effects mediate action. # 17. Falsifiability and decisive tests ## 17.1 Claim-level falsification tests ----------------------------------------------------------------------- **Claim** **Evidence that would **Consequence** count against it** ----------------------- ----------------------- ----------------------- Prior interaction Once current beliefs, Retain current-state history has a skill, expectations, constructs; remove distinctive effect recent exposure, and history as an external resources are explanatory variable. measured, history adds no held-out predictive value. Context-rich traces are Event-only models match Context fields are necessary context-rich models in unnecessary for that out-of-domain claim and grain. prediction and intervention selection for the declared claim. Typed equivalence Equivalence type and Revise or reject the predicts behavior similarity dimensions taxonomy. fail to predict performance or transfer beyond surface features and task labels. Visual structure has an Under controlled Reject the claimed early independent exposure and matched temporal mechanism. effect content, visual encoding has no reproducible effect on early attention or action after semantic knowledge is modeled. A stable primitive set The proposed primitives Treat units as exists fail compositionality, model-relative. cannot encode multiple modalities without ad hoc additions, or do not support cross-system prediction. The integration model A simpler established Reject the integration is useful model predicts held-out layer under parsimony. trajectories and intervention effects equally well or better with fewer assumptions. ----------------------------------------------------------------------- ## 17.2 Evidence that a new discipline is unnecessary A new discipline should be rejected if a preregistered research program finds that: - established constructs can be translated into the canonical ontology without explanatory loss; - a composite model built from existing theories predicts interaction and transfer across domains; - proposed new constructs add negligible, unstable, or non-replicating predictive value; - no distinctive methods are required beyond existing experimental, computational, field, and interpretive methods; - the most successful explanations remain domain-specific and do not converge on independent interaction laws; - organizing the work within HCI and adjacent fields produces cumulative results without conceptual obstruction. ## 17.3 Evidence that could justify a new discipline A positive case would require all of the following, not merely one: 43. a recurrent anomaly across multiple established theories and domains; 44. a new mechanism with precise scope and non-redundant predictions; 45. cross-implementation and cross-cultural replication; 46. superior held-out prediction and intervention selection against strong composite baselines; 47. measurement instruments and data standards that remain stable across technologies; 48. a progressive research program in which later results increase precision rather than multiply exceptions. ## 17.4 Recommended decisive benchmark Construct a multi-laboratory benchmark with at least: - three interaction modalities; - three task families; - multiple representations per semantic task; - novice, intermediate, and expert participants; - at least two linguistic or cultural settings; - immediate, retained, and transfer outcomes; - both individual and collaborative conditions; - systems with different feedback latency, initiative, and predictability. Compare four model classes on held-out systems and populations: - [M0]{.mark}: event-only statistical baseline; - [M1]{.mark}: strongest domain-specific established model; - [M2]{.mark}: integrated existing-theory model using the canonical ontology; - [M3]{.mark}: M2 plus any proposed interaction-specific construct. Use calibration, predictive accuracy, intervention success, complexity penalties, parameter recoverability, and qualitative error analysis. The independent-discipline claim receives support only if M3 wins reproducibly and the added construct has a stable interpretation across domains. # 18. Recommended sequence for foundational papers Each paper should make one primary contribution and leave a reusable artifact. ## Paper 1 - The discipline-necessity argument **Single contribution:** a formal decision standard for whether human-computational interaction requires an independent discipline. **Contents:** scope, boundary criteria, map of existing explanations, explicit negative current conclusion, and conditions for reversal. **Artifact:** discipline test checklist and evidence matrix. ## Paper 2 - Canonical ontology and terminology **Single contribution:** a minimal shared ontology that maps established theories without claiming a new mechanism. **Contents:** definitions, exclusions, typed equivalence relations, model-relative units, and mappings to HCI, cognitive science, human factors, distributed cognition, and activity theory. **Artifact:** machine-readable ontology and crosswalk table. ## Paper 3 - Context-complete interaction evidence **Single contribution:** an observation and reporting standard that distinguishes traces from evidence. **Contents:** closed-loop transition record, feasible/signaled/believed action sets, synchronization, uncertainty, provenance, and claim-dependent context. **Artifact:** open schema, coding protocol, and validation examples. ## Paper 4 - Interaction history as mediated learned state **Single contribution:** a causal test of whether exposure history has effects beyond current measured knowledge, skill, expectations, habits, and external resources. **Contents:** longitudinal design, mediator measurement, retention, forgetting, and competing models. **Artifact:** longitudinal dataset and preregistered model-comparison suite. ## Paper 5 - Typed equivalence and transfer **Single contribution:** an empirical test of which equivalence types predict positive, negative, or zero transfer across representations and systems. **Contents:** semantic, informational, task, computational, and interactional equivalence; similarity profiles; expert-novice differences. **Artifact:** cross-system transfer benchmark. ## Paper 6 - Coupled multi-timescale interaction model **Single contribution:** a formal model linking joint state, interpretation, policy, transition, feedback, and learned state. **Contents:** nested submodels, parameter identifiability, qualitative and quantitative predictions, and explicit omissions. **Artifact:** executable reference model and simulation environment. ## Paper 7 - Social and institutional extension **Single contribution:** a test of when social roles, norms, language, division of labor, and institutional constraints add predictive or explanatory value beyond individual models. **Contents:** collaborative tasks, breakdown and repair, distributed representations, multilevel models, and ethnographic validation. **Artifact:** synchronized multi-actor corpus and coding framework. ## Paper 8 - The decisive comparative test **Single contribution:** determine whether any proposed interaction-specific mechanism adds stable explanatory power beyond integrated existing theories. **Contents:** preregistered benchmark, held-out domains, model comparison, replication, and an explicit discipline decision. **Artifact:** public benchmark, model leaderboard with uncertainty, and final boundary statement. # 19. Formal argument ## 19.1 Argument against creating an independent discipline now 49. A new scientific discipline is justified only when it supports a progressive explanatory program that cannot be pursued adequately within existing disciplines. 50. The proposed domain - human interaction with computational processes - is coherent and implementation-independent when defined as reciprocal causal coupling over time. 51. Every proposed core phenomenon has an established explanatory counterpart: experience in learning and transfer; opportunity and constraint in ecological psychology, decision science, and human factors; representation and meaning in semiotics and cognitive science; context in situated action and anthropology; system coupling in cybernetics; collective organization in distributed cognition and activity theory; formal prediction in cognitive modeling and computational interaction. 52. The remaining weaknesses are primarily failures of integration, operational alignment, shared evidence standards, and cross-domain model comparison. 53. Integration failures do not by themselves establish a new mechanism, ontology, or natural kind. 54. Creating a new discipline before demonstrating conceptual irreducibility would duplicate terminology, fragment evidence, and weaken comparison with established baselines. 55. A focused research program within HCI can conduct the required ontology, measurement, longitudinal, and model-comparison work without foreclosing a later disciplinary claim. 56. Therefore, the creation of an independent discipline is not presently scientifically justified. ## 19.2 Strongest counterargument The strongest positive argument is that no existing discipline treats temporally extended human-computational coupling - including representation, learning, system agency, social context, and cross-system transfer - as its central explanandum. HCI is broad and often design-led; cognitive science may treat technology as an environment rather than a co-adaptive agent; social theories often lack formal prediction; computational models often omit meaning and institutions. A dedicated discipline could force integration and cumulative standards. ## 19.3 Response Centralization can improve coordination, but scientific necessity cannot be inferred from organizational convenience. The proposed integration can be tested as a research program. If it produces irreducible mechanisms and stable predictive laws, the evidence for a discipline will then exist. Naming the discipline first would reverse the required order: institution before necessity. # 20. Final conclusion **Interaction does not currently justify an independent scientific discipline.** It justifies a rigorous foundational research program within HCI, connected to cognitive science, human factors, learning science, and social theory. The preferred theory is therefore not a new grand system. It is the smallest integration that permits decisive comparison: - interaction as a coupled trajectory; - action interpreted relative to feasible, signaled, and believed opportunities; - representation separated from content and interpretation; - history mediated through learned state and changed environments; - equivalence specified by type; - traces converted to evidence through an observation model; - social and institutional variables included through mechanisms rather than demographic determinism; - new constructs admitted only when they add replicated predictive power. This conclusion should be reversed only by evidence that the integrated existing-theory baseline fails systematically and that a new interaction-specific mechanism succeeds across implementations. Until then, the scientifically conservative and more explanatory choice is integration rather than disciplinary proliferation. # 21. 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Representations in distributed cognitive tasks. *Cognitive Science, 18*(1), 87-122. *End of report* ======================================================================== ## FILE: docs/02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.md (1134 lines, 62.4 KiB) ======================================================================== **Research paper\ **15 July 2026\ Scope: interaction involving humans and computational systems, considered independently of particular interfaces or platforms ----------------------------------------------------------------------- **CENTRAL FINDING\ **Interaction can be treated as a primary scientific object because it denotes an observable, temporally extended pattern of reciprocal constraint and state change. Current evidence does not establish theoretical independence sufficient for an autonomous discipline. The justified next step is a dedicated comparative theoretical framework tested against integrated existing theories. ----------------------------------------------------------------------- ----------------------------------------------------------------------- # Abstract This paper asks whether interaction itself can serve as a primary object of scientific explanation rather than merely a property of humans, machines, communication, cognition, or environments. It compares the scientific structure of twelve disciplines, reviews major ways interaction is conceptualized, and evaluates formal traditions that model interaction directly. The analysis distinguishes three claims that are often conflated: that interaction is real and measurable; that it can be selected as the focal explanandum; and that it requires an independent discipline. Relational and process-centered sciences such as ecology, linguistics, cybernetics, and systems theory show that a scientific object need not be a substance. Interaction meets the descriptive requirements of a scientific object when specified as a bounded trajectory of reciprocal causal influence among distinguishable systems: events can be observed, variables measured, mechanisms proposed, models falsified, and predictions tested. However, ecological psychology, dynamical systems, control theory, distributed cognition, activity theory, conversation analysis, HCI, computational interaction, process calculi, game theory, and reinforcement learning already supply much of the necessary ontology and formal machinery. No reviewed evidence demonstrates a general interaction-specific mechanism that is irreducible to a principled combination of those frameworks, and no cross-domain benchmark establishes superior predictions from an independent theory. The evidence therefore supports treating interaction as a primary scientific phenomenon and organizing a dedicated comparative theoretical program, but not yet an autonomous science. The paper ends with the minimum ontology and empirical tests needed to decide whether theoretical independence emerges. **Keywords:** interaction; scientific object; HCI; cybernetics; systems theory; ecological psychology; computational interaction; ontology; process theory # 1. Introduction The expression "interaction" appears across nearly every science. Particles interact through fields; molecules interact through bonds and reactions; organisms interact with environments; speakers interact through language; people interact with machines; and processes interact through communication and synchronization. Ubiquity, however, does not establish scientific independence. A term may identify a mechanism inside another theory, a relation among already accepted entities, a descriptive label, or a genuine phenomenon whose regularities warrant direct explanation. The central question is therefore not whether interaction matters. It is whether interaction can be made the subject of explanations in which the interaction trajectory, rather than either participant considered separately, is the principal dependent object. This requires a stricter test than demonstrating that interaction is observable. Scientific work routinely studies relations without granting each relation a separate discipline. Conversely, ecology, linguistics, and cybernetics demonstrate that a field may legitimately organize around relations, processes, or patterns rather than material substances. This paper distinguishes a primary scientific object from an autonomous scientific domain. A primary object is a stable class of phenomena selected as the focal target of measurement and explanation. An autonomous domain additionally requires theoretical independence: characteristic mechanisms, explanatory questions, and cumulative models that cannot be replaced without loss by existing disciplines. The distinction permits a positive answer to the object question without presupposing a new discipline. The paper\'s single contribution is a conditional determination: interaction is scientifically admissible as a primary object, but the evidence presently supports a distinct theoretical program rather than a distinct discipline. That determination is based on comparative structure, not on the existence of a community or the novelty of terminology. # 2. What Constitutes a Scientific Object? A scientific object is not simply anything that exists. It is an empirically tractable target stabilized by definitions, instruments, measurement conventions, models, and explanatory practices. Electrons, genes, species, grammatical structures, memory, and ecosystems differ ontologically, yet each becomes scientifically usable through operations that identify instances, distinguish variables, and connect observations to mechanisms. Four conditions are necessary. First, an object must have identity conditions: researchers must be able to state what counts as an instance and where the object begins and ends. Second, it must support observation or warranted inference through an explicit observation model. Third, it must enter reproducible explanatory relations: changes in specified conditions should imply differences in measurements or distributions. Fourth, theories about it must be vulnerable to evidence. These conditions do not require perfect consensus or direct visibility. They require disciplined correspondence among definitions, observations, and claims. A stronger condition applies when a proposed object is used to justify a new scientific domain. It must supply incremental explanatory power. Its characteristic variables or mechanisms must outperform, simplify, unify, or otherwise materially improve on established accounts. Institutional novelty, terminological fragmentation, and interdisciplinary inconvenience do not meet that standard. For this study, interaction qualifies as a primary object only if it can be individuated independently of a named interface, measured as more than a list of participant properties, and modeled such that the trajectory has explanatory properties not captured by a static description of its participants. It qualifies as the basis of an independent domain only if these models require indispensable constructs or mechanisms absent from existing theories. # 3. How Existing Sciences Define Their Objects Table 1 compares scientific structure rather than disciplinary history. "Observer" identifies the investigator or measurement system; "observed" identifies the focal target. The rows are ideal types: each discipline contains internal disagreement and subfields that cross the stated boundary. -------------------------------------------------------------------------------------------------------------------------- **Discipline** **Primary **Observer / observed** **Fundamental **Typical **Primary mechanisms** scientific entities and explanatory object** relations** questions** ---------------- ----------------- --------------------------- ------------------ ----------------- ---------------------- Physics Physical states Observer: instrumented Particles, fields, What changes? Dynamical laws, and lawful investigator or detector. spacetime, energy, Under what forces/fields, quantum changes of Observed: physical systems momentum; forces, invariances and interactions, matter, energy, and events. symmetries, laws? What conservation and fields, space, conservation, produces motion, symmetry breaking. and time. interaction. structure, or transition? Chemistry Composition, Observer: chemist and Atoms, molecules, Why does a Bonding, electron structure, analytical apparatus. ions, bonds, substance have structure, properties, and Observed: substances, phases; reaction these properties? thermodynamics, transformations molecular systems, and equilibrium Which kinetics, catalysis, of matter. reactions. relations. transformations molecular collision. occur, at what rates and yields? Biology Living systems Observer: biological Cells, organisms, How is life Evolution, gene and the processes investigator. Observed: genes, traits, organized, expression, that sustain, molecules, cells, populations; maintained, metabolism, reproduce, organisms, lineages, inheritance, developed, regulation, develop, and populations. regulation, inherited, and development, selection diversify them. competition, changed? and drift. cooperation. Ecology Relations among Observer: ecologist with Organisms, What determines Selection, resource organisms and field, experimental, populations, distribution, limitation, trophic between organisms remote, or model-based resources, abundance, interaction, and environments instruments. Observed: habitats; persistence, and disturbance, feedback, across levels. populations, communities, predation, ecosystem dispersal, succession. ecosystems and flows. competition, organization? mutualism, energy and matter flow. Linguistics Language as Observer: linguist, corpus, Phonological, What structures Grammar, structured human experiment, field morphological, are possible? How compositionality, capacity, system, elicitation. Observed: syntactic, are form, inference, learning, and use. utterances, judgments, semantic and meaning, use, interactional practices, structures. pragmatic units; acquisition, and organization, combinatorial and change related? historical change. contextual relations. Psychology Mind and behavior Observer: researcher and Percepts, Why do Perception, attention, of humans and behavioral/physiological memories, beliefs, individuals memory, learning, other animals. instruments. Observed: goals, actions; perceive, learn, motivation, decision, behavior and inferred causal and decide, feel, and development, neural mental processes. statistical act as they do? and social processes. relations among organism and context. Human Factors Human Observer: analyst, Humans, tasks, How do system Attention and capabilities, experimenter, or tools, conditions shape workload, control limitations, and operational monitoring organizations; safety, loops, performance system. Observed: workload, control, effectiveness, skill-rule-knowledge within work and person-system performance. error, reliability, and behavior, automation, technological coordination and well-being? joint cognitive work. systems. constraint. Human-Computer Use, design, Observer: HCI researcher, Users, How do people use Cognitive, ecological, Interaction experience, and designer, logs, laboratory computational and experience social, consequences of or field methods. Observed: artifacts, tasks, computing, and organizational, interactive people, artifacts, representations, how can economic and computing. practices and interaction actions, contexts; interactive computational episodes. usability and systems be mechanisms; design experiential explained or interventions. relations. designed? Cognitive Cognition and Observer: interdisciplinary Representations or How is Computation, Science intelligence investigator and dynamical states, intelligent representation, neural across biological behavioral, neural, algorithms, behavior processing, Bayesian and artificial linguistic or computational bodies, generated, inference, dynamical systems. instruments. Observed: environments, learned, coupling, embodied cognitive systems and agents; represented, action. performances. computation, embodied, and inference and distributed? coupling. Information Properties, Observer: information Documents, How is Indexing, Science behavior, flow, scientist and signals, records, information classification, organization, documentary/computational metadata, users, generated, retrieval, retrieval, use, systems. Observed: collections; organized, communication, and effects of information objects, users, relevance, communicated, information behavior, information. institutions and processes. retrieval, found, social and technical communication and interpreted, and mediation. transformation. used? Cybernetics Control and Observer may be first-order Systems, signals, How does a system Negative/positive communication in external analyst or goals, regulate itself, feedback, control, animals, second-order disturbances, maintain estimation, machines, and participant-observer. sensors, variables, adapt, communication, organizations. Observed: regulatory controllers; or communicate adaptation and systems and feedback feedback, under recursion. relations. requisite variety, disturbance? circular causation. Systems Theory Organization, Observer: modeler who Components, How do Feedback, network relations, declares system boundary boundaries, organization and structure, hierarchy, boundaries, and level. Observed: states, relations self-organization, emergence, and organized wholes and inputs/outputs, generate nonlinearity, change in systems component relations. networks; system-level emergence and across domains. hierarchy, behavior across adaptation. coupling, scales? emergence and constraint. -------------------------------------------------------------------------------------------------------------------------- The comparison yields three conclusions. First, mature sciences are not distinguished solely by ontological type. Physics and chemistry emphasize substances and states; ecology emphasizes relations and populations; linguistics emphasizes structured capacities and products; cybernetics emphasizes circular processes. A relational phenomenon is therefore not disqualified from primary status. Second, interaction is already a primary term inside several disciplines. Ecology directly studies organism-environment and organism-organism relations. Human factors officially defines itself around interactions among humans and system elements. HCI explicitly studies the human-computer interaction process. Cybernetics treats communication and feedback loops as the central phenomenon. Interaction is therefore not scientifically homeless. Third, disciplines differ less by exclusive ownership of entities than by characteristic explanatory questions, boundary conventions, mechanisms, and evidence. Biology uses physical and chemical entities but asks biological questions. Ecology uses organisms already studied by biology but makes their relations and population-level consequences focal. The relevant test for interaction is consequently whether making the trajectory focal produces distinctive, cumulative explanations that are not merely renamed ecology, cognition, control, communication, or system dynamics. # 4. How Interaction Is Currently Treated ## 4.1 Competing ontological roles - **Object:** The interaction episode or trajectory is itself bounded, compared, and explained. Common in conversation analysis, interaction analysis, HCI studies, and some computational models. - **Process:** Interaction is reciprocal influence unfolding over time. This is dominant in dynamical systems, ecological psychology, enactivism, cybernetics, and situated action. - **Relationship:** Interaction denotes a relation between entities, often without asserting a separate object. Ecology, sociology, and network analysis frequently use this form. - **Mechanism:** Interaction is a causal means through which outcomes arise: molecular collision, feedback, social influence, signaling, or human-machine coordination. - **Property:** A system is described as interactive, coupled, responsive, or open. The property belongs to a system architecture rather than to an episode. - **Outcome:** Interaction is measured through engagement, coordination, influence, or exchange produced by prior conditions. - **Metaphor:** "Dialogue," "conversation," "partnership," and "ecology" are sometimes transferred to systems without the commitments of the source theory. Metaphorical use is productive for design but insufficient for scientific identity. ## 4.2 Philosophical assumptions Representational accounts treat interaction as information exchange among systems that possess internal states, goals, and mappings. Classical cognitive HCI, information-processing psychology, agent models, and many semantic ontologies take this form. Their strength is decomposition and prediction; their risk is treating context and material organization as inputs to an otherwise self-contained processor. Ecological and enactive accounts treat interaction as organism-environment coupling in which perception and action are co-defined. Affordances are relational possibilities for action rather than properties of an object alone. Their strength is direct treatment of embodiment and environment; their risk is underspecifying symbolic interpretation, institutional structure, or computational architecture. Dynamical and cybernetic accounts treat interaction as coupled state change, feedback, regulation, and mutual constraint. They provide precise temporal and mathematical tools. Their risk is explanatory thinness when goals, meanings, norms, and historical practices are compressed into state variables without an account of their constitution. Situated, distributed, and activity-theoretical accounts place interaction within material, social, historical, and organizational systems. They explain how action is mediated by artifacts, rules, communities, plans, representations, and division of labor. Their strength is boundary expansion; their risk is difficulty producing compact cross-domain predictions. Pragmatic and interactional linguistic accounts treat meaning as publicly achieved through sequences of action, inference, turn-taking, repair, and common ground. They show that an utterance\'s meaning is not exhausted by its encoded content. Their risk, for a general interaction science, is domain restriction to communicative and socially accountable action. Formal computer science treats interaction as communication, synchronization, observation, and response among computational processes or between system and environment. Process calculi, automata, game semantics, protocol models, and coalgebra provide representation-independent descriptions with strong compositionality and verification. They generally abstract away from human perception, learning, embodiment, and culture. # 5. Systematic Literature Review ## 5.1 Review design The review was structured as a theory-oriented scoping review rather than a meta-analysis. Searches targeted the terms interaction theory, interaction ontology, formal interaction model, interaction grammar, interaction primitives, interaction semantics, interaction machines, computational interaction, agent-environment coupling, social interaction, conversation analysis, process algebra, game semantics, cybernetics, ecological psychology, distributed cognition, situated action, activity theory, and human-computer interaction. Sources were selected when they proposed definitions, ontologies, formal mechanisms, or explicit boundaries, rather than merely reporting a designed system. Priority was given to primary or field-defining sources: Wiener on cybernetics; von Bertalanffy on general systems; Gibson on affordances and ecological information; Card, Moran, and Newell on quantitative HCI; Suchman on situated action; Hutchins on distributed cognition; Sacks, Schegloff, and Jefferson on turn-taking; Milner and Hoare on process calculi; Abramsky and colleagues on game semantics; and contemporary work on computational interaction and computational rationality. Professional definitions from the International Ergonomics Association, ACM SIGCHI, American Chemical Society, Ecological Society of America, Linguistic Society of America, and American Psychological Association were used only to characterize declared disciplinary objects. The review sought contradictory evidence in two directions. Evidence against primary-object status included accounts that reduce interaction without loss to participant states, communication, cognition, control, or task performance. Evidence against a new discipline included frameworks that already supply a complete-enough ontology, mechanisms, measurement, and prediction. Evidence supporting primary-object status included relational effects, path dependence, emergence, and coordination patterns that cannot be inferred from participant properties considered independently. This is not an exhaustive database review. Search coverage was broad across traditions but uneven across languages and publication venues. The assessment therefore concerns the theoretical record located and the standards it meets, not the absence of every possible prior formulation. ## 5.2 Major formalization traditions **Cybernetics and control theory.** Interaction is a closed causal loop involving plant, controller, sensor, goal/reference, disturbance, and feedback. Strong on measurable dynamics, stability, adaptation, and intervention. Weak on semantic interpretation and social constitution unless supplemented. **Dynamical systems and coordination dynamics.** Interaction is coupled evolution in a joint state space. Strong on emergence, synchronization, phase transitions, and multi-scale time. Weak when state variables lack independently validated psychological or social meaning. **Ecological psychology and enactivism.** Interaction is organism-environment reciprocity; action possibilities are relational and perception is oriented toward action. Strong on embodiment, environmental structure, and mutuality. Weak on formal semantics, institutions, and many computational representations. **Conversation analysis and interactional linguistics.** Interaction is sequentially organized social action, including turn construction, adjacency, preference, repair, and accountability. Strong on endogenous evidence and public organization. Limited generality beyond socially interpretable conduct. **Activity theory, situated action, distributed cognition.** Interaction is mediated action within historically developed activity systems and distributed cognitive arrangements. Strong on artifacts, context, organizational roles, and development. Formal predictive comparison remains difficult. **Classical cognitive HCI.** Interaction is decomposed into goals, operators, methods, selections, perceptual/motor/cognitive processors, and task structures. Strong on quantitative prediction for practiced tasks. Limited for open-ended interpretation and social change. **Computational interaction and computational rationality.** Interaction is modeled using optimization, probabilistic inference, control, machine learning, cognitive models, and resource-bounded rationality. Strong on explicit generative models and design-relevant prediction. Often requires task-specific objective functions and representations. **Process calculi, automata, protocol theory, and interaction machines.** Interaction is communication and state transition among open processes. Strong on compositional semantics, equivalence, liveness, safety, and verification. Human meaning and learning are normally outside scope. **Game theory and game semantics.** Interaction is strategic or logical exchange among players/system and environment. Strong on incentives, information structure, strategies, and compositional meaning. Assumptions about rationality or formal moves can be restrictive. **Multi-agent and semantic ontologies.** Interaction is represented through agents, actions, commitments, roles, messages, services, and protocols. Strong on machine-readable interoperability. Ontologies usually encode domain commitments rather than establish natural scientific mechanisms. # 6. Comparative Analysis ## 6.1 Does interaction have identity conditions? Interaction is not individuated merely by temporal co-occurrence. Two systems may change simultaneously without interacting. A defensible minimum criterion is counterfactual reciprocal dependence: during a bounded interval, a state or action of at least one participant alters the probability distribution over subsequent states, observations, or actions of another, and the resulting change can in turn condition later behavior in the joint trajectory. Reciprocity may be delayed, asymmetric, intermittent, mediated, or distributed; it need not occur in every adjacent event. This definition separates interaction from one-way influence while allowing unequal agency. It also makes boundary selection explicit. An episode is bounded by an analytic rule such as task onset and completion, stabilization, conversational sequence closure, loss of causal coupling, or an experimentally imposed interval. Different boundaries may be legitimate for different questions, as in ecology and systems science, but they must be declared and tested for robustness. The interaction object is therefore a trajectory over a joint state space, together with the coupling relations that generate it. It is not a third substance inserted between participants. Its identity resembles a reaction, conversation, control loop, or ecosystem process: a structured occurrence whose properties depend on relations and history. ## 6.2 Can interaction-level properties be non-reducible? Several established phenomena support interaction-level description. Coordination can exhibit synchrony, entrainment, turn organization, escalation, deadlock, mutual adaptation, repair, and convention formation. These properties are not attributes of either participant alone. They depend on coupling topology, timing, information availability, and history. Knowing each participant\'s isolated capability is generally insufficient to determine the joint trajectory. Non-separability does not prove ontological independence. The joint behavior may still be explained completely by participant models plus coupling laws. In physics, a collision is a legitimate object of analysis even when the theory reduces it to fields and particles. Likewise, interaction can be primary for measurement and explanation without requiring fundamental primitives beyond agents, environments, states, actions, and coupling. The strongest case for theoretical independence would be a law or mechanism whose explanatory role cannot be preserved by any reasonable decomposition into participant dynamics and established coupling theories. The reviewed literature does not yet provide such a result. Emergence, path dependence, and circular causation motivate interaction-level models, but systems theory, cybernetics, dynamical systems, ecology, and social interaction research already accommodate them. ## 6.3 Criteria assessment ------------------------------------------------------------------------------ **Criterion** **Evidence **Evidence limiting** **Assessment** supporting** ----------------- ------------------- ---------------------- ----------------- Identifiable Reciprocal causal Boundaries and Satisfied natural phenomena episodes occur granularity are conditionally. across biological, observer-relative; social, and "interaction" is too computational broad without a domain settings; coupling and identity rule. can be operationally bounded. Observable events Actions, messages, Meaning, belief, Satisfied. state changes, intention, and timing, feedback, perceived opportunity repair, and are latent and require outcomes can be observation models. recorded. Measurable Latency, transition Measures are Satisfied, not variables probabilities, tradition-specific and yet standardized. information flow, often not invariant synchrony, error, across contexts. utility, workload, learning, and coordination are measurable. Reproducible Regularities exist Open social settings Partly satisfied. behavior in motor and adaptive systems performance, can be historically turn-taking, contingent and feedback control, nonstationary. learning, and protocol behavior. Explanatory Feedback, Mechanisms come from Satisfied through mechanisms affordance, adjacent disciplines; integration. inference, no uniquely learning, interaction-specific coordination, mechanism is communication, demonstrated. constraint, and strategic adaptation are established. Predictive GOMS/KLM, control No single theory Partly satisfied. capability models, process predicts heterogeneous models, interaction across computational tasks, modalities, rationality, game cultures, and time theory, and scales. dynamical models predict bounded classes. Empirical Models imply Broad verbal Satisfied for testability intervention, interaction frameworks formalized trajectory, timing, can evade decisive claims. error, transfer, comparison if boundary and adaptation and measures are predictions. unspecified. Theoretical Interaction-level Existing frameworks Not established. independence variables organize already represent phenomena missed by coupling, isolated communication, participant coordination, descriptions. emergence, and learning. Incremental superiority is unshown. ------------------------------------------------------------------------------ # 7. Arguments Supporting Interaction as a Scientific Object **Relational objects are scientifically legitimate.** Ecology treats relationships among organisms and environments as its declared object; cybernetics treats feedback and communication as central; linguistics studies structured relations between form, meaning, and use. Scientific objects need not be material substances. **The trajectory contains information absent from snapshots.** Sequence, latency, mutual adaptation, repair, and path dependence cannot be reconstructed from static participant attributes alone. The ordering of events can change outcomes even when initial and final states match. **Interaction supports intervention.** Researchers can manipulate coupling strength, feedback delay, action availability, information asymmetry, representation, incentives, and protocol rules, then measure predicted changes in trajectories. This supports causal rather than merely descriptive inquiry. **Interaction admits multiple formal representations.** State-transition systems, differential equations, stochastic processes, process algebras, games, information-theoretic measures, and generative cognitive models can represent interaction without dependence on a particular interface. **Cross-domain regularities are plausible.** Feedback, coordination, exploration, adaptation, breakdown, repair, and convention formation recur in biological, social, and computational systems. Whether these regularities support a unified theory is an empirical question, but they define a coherent comparative program. **Observer participation can be modeled.** Second-order cybernetics, ethnomethodology, and measurement theory show that observer dependence need not invalidate an object. It requires explicit boundary, instrument, coding, and reflexivity assumptions. # 8. Arguments Against **Excessive extension.** If interaction includes every causal relation, the object becomes coextensive with science and loses discriminatory value. A domain must restrict participants, coupling, scale, and explanatory questions. **Redescription without mechanism.** Calling a sequence an interaction does not explain it. Established mechanisms - perception, learning, control, communication, incentives, norms, and computation - may already provide all causal content. **Observer-imposed boundaries.** Episodes, agents, and environments may be analytically selected rather than naturally segmented. Different choices can produce different interaction descriptions and apparent laws. **Heterogeneous mechanisms.** Molecular interaction, social negotiation, and human-computer use may share only an abstract pattern of mutual influence. A theory general enough to include all may become too weak to predict any. **Existing integrative frameworks.** Systems theory, cybernetics, ecology, cognitive science, distributed cognition, and HCI already study organized relations across components. A new framework must beat their principled combination, not isolated caricatures. **No demonstrated predictive increment.** The literature contains strong local models but no accepted benchmark in which a general interaction theory yields replicated out-of-domain predictions superior to integrated existing models. **Institutional criteria are not scientific criteria.** A journal, program, ontology, or professional identity can be useful without establishing a new natural kind or autonomous explanatory domain. # 9. Attempted Falsification: Are Existing Theories Already Complete? The strongest negative hypothesis is that an interaction episode is fully explained by: (1) participant state-transition models; (2) an environment model; (3) communication and observation channels; (4) coupling rules; and (5) established mechanisms for learning, control, decision, and social organization. On this view, "interaction" is a convenient projection of an already complete joint model. Formal computer science supports much of this hypothesis. Open systems can be modeled as automata or processes whose observable behavior is defined through communication with an environment. Process calculi provide composition, equivalence, safety, and liveness. Game semantics gives meaning through structured exchanges between system and context. Control and dynamical systems provide joint trajectories and feedback. Reinforcement learning and partially observable decision processes provide action, observation, reward, belief update, and adaptation. Multi-agent systems add strategic dependence and communication. Behavioral and social theories fill additional gaps. Ecological psychology supplies relational action possibilities; cognitive science supplies perception, memory, inference, and learning; conversation analysis supplies sequence organization and repair; activity theory supplies motive, mediation, rules, community, and development; distributed cognition supplies representational coordination across people and artifacts; human factors supplies joint performance and safety; HCI provides domain methods and empirical phenomena. Taken together, these frameworks can express every item in the candidate ontology. This is substantial evidence against an independent discipline. Yet expression is not equivalent to a completed explanation. The frameworks use incompatible boundaries, units, semantics, and validation practices. Their combination is usually verbal rather than generative, and it is rarely tested as a composite baseline. The completeness claim therefore remains unproven in the same way as the independence claim. A decisive falsification program would construct the strongest integrated baseline available, not compare a new theory against one narrow field. If participant-plus-coupling models predict interaction trajectories, transfer, breakdown, and intervention outcomes across domains as well as any interaction-centered theory with equal or lower complexity, the independent-framework hypothesis should be rejected. If systematic residuals remain and require a stable new mechanism, the positive case strengthens. # 10. Minimum Ontology if Interaction Is the Focal Object The ontology below is a translation layer assembled from established vocabulary. It is not evidence for the conclusion and does not claim that every construct is fundamental. A new construct is warranted only where existing terms fail under empirical comparison. --------------------------------------------------------------------------- **Concept** **Established **Overlap / gap** **New construct equivalents and required?** definition** ----------------- ------------------- ------------------- ----------------- Agent Organism, actor, Agency ranges from No. user, controller, intentional human process, action to participant: a rule-governed system capable of process behavior; state-dependent the intended level action or response. must be declared. Environment Surround, context, Boundary is No. world, task analytic and may environment: move; social and conditions outside computational the focal agent elements can be boundary that agent or affect or are environment affected by it. depending on question. State System state, joint No state No. state, belief description is state, situation: theory-neutral; variables latent human state sufficient for the requires model\'s future measurement evolution at a assumptions. chosen grain. Semantic state Belief, The phrase risks No umbrella term interpretation, reifying meaning as needed. common ground, task an internal object; meaning, content distinguish public state: content, agent meaning-relevant belief, and analyst distinctions coding. attributed to an agent or public interaction. Representation External Representation may No. representation, be internal, sign, signal, external, display, symbol, conventional, inscription: a form indexical, or preserving action-based; distinctions that theory must state can be perceived or commitments. manipulated. Opportunity Affordance, action Physical No new root possibility, feasibility, system construct; use option, enabled permission, typed action action: a relation perceptual sets. specifying actions signaling, and possible for an agent belief are agent under current often conflated. constraints. These should be separated. Action Act, operation, Intentional and No. move, control nonintentional input, utterance: actions require an event different attributable to an attribution rules. agent that can alter joint state or information. State transition Reaction, event, May be discrete, No. update, transition: continuous, change from one stochastic, or state to another socially under actions, constituted. dynamics, and disturbances. Observation Percept, signal, Agent observation No. measurement, and researcher feedback channel observation must be output: information kept separate. made available to an agent or researcher. Feedback Action-contingent Not every No. observation that observation is can regulate feedback; causal subsequent dependence on prior behavior. state/action matters. Adaptation Learning, Change may occur in No. accommodation, human, policy update, computational, plasticity, environmental, or co-adaptation: institutional persistent change components and at induced by different time experience. scales. Interaction Conversation, Needed as the focal A precise episode trial, encounter, observational unit; definition is session, coupled boundaries remain required, but the trajectory: an claim-dependent. vocabulary analytically exists. bounded interval of reciprocal causal influence. Evidence Observation that Raw event logs are No. discriminates among data, not claims under an self-interpreting explicit evidence. observation and validity model. --------------------------------------------------------------------------- # 11. Minimum Formal Object At a declared time scale, let an interaction model contain agents A = {a1 \... an}, an environment E, a joint external state x_t, agent-specific observations o_i,t, actions u_i,t, internal or learned states h_i,t, and a transition rule P(x\_{t+1} \| x_t, u_1,t \... u_n,t, E_t). Observation functions map joint state to what each agent can detect. Policies map observations, internal state, goals, and constraints to action distributions. Learning rules update persistent agent state. Context variables specify social, institutional, linguistic, and physical conditions not otherwise included. An interaction episode is a bounded trajectory I = \ plus the declared coupling structure. It is interactive when cross-component dependence exceeds a specified null model: at least one participant\'s action or state changes the conditional distribution of another participant\'s later observations, states, or actions, and the resulting trajectory contains a return path or reciprocal dependence within the episode or across linked episodes. This template is intentionally compatible with control systems, stochastic games, dynamical systems, process models, cognitive architectures, conversation sequences, and qualitative process tracing. It does not assert that every meaningful variable is numerical. It does require that each proposed variable have a stated observation or inference rule. The model\'s scientific value lies in comparisons. Candidate interaction-level variables - coordination regime, repair state, convention, coupling strength, or path-dependent joint strategy - must improve held-out prediction or causal explanation beyond participant and environment variables. Otherwise they are descriptive summaries rather than indispensable constructs. # 12. Required Empirical Program 1. **Boundary robustness:** Test whether conclusions survive reasonable changes in episode boundary, agent definition, and temporal grain. 2. **Composite baseline comparison:** Compare interaction-centered models against the strongest integrated model from cognition, control, communication, learning, social organization, and system dynamics. 3. **Cross-representation invariance:** Hold task and semantic content constant while changing visual, auditory, linguistic, or physical representation. Determine which trajectory properties transfer. 4. **Cross-system prediction:** Fit models in one computational system and predict behavior in another without redefining core constructs. 5. **Longitudinal co-adaptation:** Measure human learning, computational adaptation, and environmental change jointly rather than treating one side as stationary. 6. **Intervention on coupling:** Manipulate feedback delay, observability, initiative, constraints, or communication topology and test predicted regime changes. 7. **Interaction-level residual test:** After modeling participant states and coupling, test whether stable residual structure remains that is captured by an interaction-specific construct. 8. **Measurement invariance:** Test whether constructs retain comparable meaning across cultures, languages, expertise levels, occupations, and access conditions. 9. **Failure criterion:** Reject the dedicated framework when established composite models achieve equal or better prediction, intervention selection, and explanatory compression with fewer assumptions. # 13. Threats to Validity Conceptual breadth is the principal threat. Interaction ranges from physical force exchange to social meaning-making. The paper mitigates this by restricting its operational conclusion to bounded reciprocal causal trajectories and by requiring domain declarations. The abstraction may still conceal mechanisms too heterogeneous for a common theory. Source selection may favor traditions that already formalize interaction. Important work in anthropology, sociology, communication, robotics, organizational science, biology, and philosophy may not be fully represented. The conclusion is therefore calibrated to the evidence reviewed, not to an assertion of exhaustive coverage. Disciplinary descriptions are simplified. Every listed field contains competing ontologies and methods. The comparison identifies dominant scientific structures rather than legislating a single correct definition. Formal tractability can bias the analysis toward measurable state-transition accounts. Meaning, normativity, identity, power, and historical development may resist compact formalization while remaining causally indispensable. The proposed empirical program therefore permits qualitative and mixed observation models, provided their inferential warrants are explicit. Theoretical independence is difficult to prove negatively. Failure to find an irreducible mechanism does not show that none exists. Conversely, fragmentation and lack of integration do not prove that one does. The paper treats both claims as open to comparative testing. The use of human-computational interaction as the motivating domain may overstate the generality of conclusions about interaction in other sciences. The proposed object definition is general, but the recommended research program should be evaluated first in domains where human and computational processes reciprocally adapt. # 14. Discussion The evidence resolves the central ambiguity by separating focality from fundamentality. Interaction can be focal because scientists can identify episodes, manipulate coupling, measure trajectories, and test mechanisms. It need not be fundamental in the metaphysical sense, and it need not displace agents, environments, cognition, communication, or computation. Reactions are primary objects for chemistry without being independent of physics; ecosystems are primary objects for ecology despite being composed of biological and physical entities. Scientific usefulness depends on explanatory organization, not ontological isolation. Interaction becomes scientifically distinctive when the explanandum is the organization of mutual influence over time: why a trajectory stabilizes, diverges, coordinates, breaks down, repairs, transfers, or changes its own future coupling. These questions cannot be answered by listing interface events or participant attributes. They require joint state, information availability, action opportunity, feedback, history, and multi-scale adaptation. Yet the ontology needed to ask those questions is not novel. Established theories already supply agents, environments, states, representations, affordances or action sets, actions, transitions, observations, feedback, adaptation, communication, strategy, context, and evidence. The scientific deficit is not missing nouns. It is the absence of a shared comparative framework in which different mechanisms make commensurable predictions about the same trajectories. This finding argues against premature discipline formation. A new discipline would impose institutional boundaries before theoretical boundaries are demonstrated. It could encourage renaming established concepts, weaken engagement with mature methods, and make negative evidence harder to recognize. A dedicated theoretical framework is a smaller and more falsifiable commitment. It can remain inside HCI and cognitive science while drawing formal machinery from systems, control, ecology, linguistics, and computer science. The framework should earn independence only through residual explanatory success. It must identify interaction-level variables that are stable across implementations, operationally distinct from participant variables, and predictively useful after strong baselines are included. The central benchmark is not whether a new vocabulary can describe more phenomena. It is whether it predicts or explains them with greater accuracy, transfer, or parsimony. # 15. Conclusion Interaction can be treated as a primary scientific phenomenon. It has identifiable instances when defined as a bounded trajectory of reciprocal causal influence; it produces observable events; it supports measurement, intervention, mechanism, prediction, and falsification; and mature sciences demonstrate that relations and processes can legitimately serve as primary objects. The evidence does not support an autonomous science of interaction at present. Existing disciplines collectively provide the relevant entities, mechanisms, formalisms, and methods. Their integration is incomplete, but incompleteness of synthesis is not evidence of theoretical independence. No reviewed framework demonstrates a uniquely interaction-specific mechanism or replicated predictive increment over a strong composite baseline. The justified scientific action is therefore to treat interaction as the focal explanandum of a dedicated comparative theoretical program. That program should use established terminology, define interaction episodes and observation models precisely, compare formal alternatives on shared data, and accept elimination if integrated existing theories prove sufficient. ----------------------------------------------------------------------- **FINAL ASSESSMENT\ 3. Interaction appears to satisfy the requirements of a distinct scientific object but additional theory is required.** ----------------------------------------------------------------------- ----------------------------------------------------------------------- # References Abramsky, S. (2013). Semantics of interaction. arXiv:1312.0121. American Chemical Society. (2026). Chemistry is everywhere: What is chemistry? American Psychological Association. (n.d.). Psychology. APA Dictionary of Psychology. Ashby, W. R. (1956). An introduction to cybernetics. Chapman & Hall. Bertalanffy, L. von. (1968). General system theory: Foundations, development, applications. George Braziller. Borko, H. (1968). Information science: What is it? American Documentation, 19(1), 3-5. https://doi.org/10.1002/asi.5090190103 Card, S. K., Moran, T. P., & Newell, A. (1983). The psychology of human-computer interaction. Lawrence Erlbaum Associates. Chemero, A. (2009). Radical embodied cognitive science. MIT Press. 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Cognitive Science, 18(1), 87-122. ======================================================================== ## FILE: docs/02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.md (979 lines, 64.2 KiB) ======================================================================== **How Sciences Define Their Objects** *Toward a General Architecture of Scientific Explanation* **Formal comparative research paper** July 2026 # Abstract This paper asks whether mature sciences share a general architecture by which they define and organize primary objects of explanation. A comparative analysis of eighteen natural, social, formal, engineering, and interdisciplinary fields is combined with a review of major accounts of scientific explanation, theory change, scientific objects, natural kinds, mechanisms, levels, experimentation, and disciplinary formation. The comparison does not support a universal object-centered template. Disciplines may be organized around entities, processes, relations, problem classes, methods, or constructed systems; historical sciences need not make precise novel predictions; and mechanism is not the exclusive form of explanation. A weaker but stable architecture does emerge. Mature sciences stabilize inquiry by coordinating seven functions: (1) a delimited domain of phenomena and explanatory targets; (2) units, levels, and scope conditions; (3) ontological commitments concerning relevant entities, properties, relations, and processes; (4) epistemic access through observations, measurements, instruments, records, and interventions; (5) public representations such as classifications, models, diagrams, equations, and simulations; (6) explanatory dependencies expressed as laws, mechanisms, causes, structures, functions, histories, computations, or statistical relations; and (7) success constraints governing evidence, comparison, prediction or retrodiction, intervention, unification, and error correction. These functions are stabilized socially through exemplars, standards, institutions, and trained communities, but community organization is a condition of disciplinary persistence rather than a component of every scientific explanation. The architecture is therefore functional and relational, not a fixed inventory of objects. Applied as a worked example, interaction is structurally compatible with scientific treatment because it can supply phenomena, units, measurements, representations, and candidate dependencies. Structural compatibility alone does not establish theoretical autonomy or justify a new discipline. The answer is qualifiedly affirmative: mature sciences exhibit a general architecture of stabilization, but not a single universal ontology or explanatory form. Primary contribution: mature sciences do not share one kind of object, but they do converge on a minimal architecture that stabilizes explanatory targets by coordinating ontology, epistemic access, representation, explanatory dependence, and evidential success. # Introduction Scientific disciplines are often described as if each were defined by a noun: physics studies matter and energy, biology studies life, linguistics studies language, and psychology studies mind and behavior. Such formulations are useful administratively but weak philosophically. They obscure disagreements over what the named object is, which level is primary, how it becomes observable, what forms of explanation count, and why some fields organized around methods or problems nevertheless function as sciences. The research question is therefore not whether disciplines can be assigned labels. It is whether mature sciences repeatedly solve a common organizational problem: how to select phenomena as explananda, delimit a domain, posit or construct objects, obtain epistemic access, represent dependencies, and evaluate explanations. A genuine general architecture must survive counterexamples from historical, formal, social, engineering, and interdisciplinary sciences. It must also distinguish a scientific object from a scientific discipline. An object may be studied by several disciplines, while one discipline may address several objects. The paper uses \'scientific object\' in a deliberately non-realist-neutral sense: a relatively stable target of systematic inquiry that is individuated through theory and practice and can support intersubjective claims. The definition does not require that every object be directly observable, a natural kind, mind-independent in the strongest metaphysical sense, or unique to one discipline. \'Explanandum\' denotes the phenomenon, regularity, event, pattern, capacity, or outcome to be explained. \'Architecture\' denotes the smallest recurring set of functions needed to organize sustained explanation, not a historical sequence every science must follow. Methodologically, the analysis combines structured comparison with philosophical synthesis. The disciplinary survey samples natural, historical, social, formal, applied, and interdisciplinary fields. For each field it identifies the dominant target, unit, ontology, relations, mechanisms or alternative dependencies, evidence, and predictive forms. The philosophical review treats competing accounts as constraints rather than selecting one school in advance. The proposed architecture is retained only where it describes every surveyed field without forcing all sciences into the image of experimental physics. # Problem Statement A theory of scientific organization can fail in two opposite ways. It can be too strong, requiring a single natural object, universal laws, controlled experiments, or novel predictions and thereby excluding geology, evolutionary biology, parts of astronomy, anthropology, computer science, and design-oriented sciences. Or it can be too weak, listing generic features such as evidence and explanation that distinguish little. The problem is to identify recurring structure without erasing genuine pluralism. Four distinctions control the analysis: - Scientific object versus object of a discipline: electrons can be objects of physics, chemistry, materials science, and engineering; no ownership relation follows. - Ontology versus methodology: what a field claims exists or matters is distinct from how it obtains evidence. - Explanandum versus unit of analysis: a field may explain population change while measuring organisms, genes, or demographic rates. - Discipline versus research program: disciplines are durable institutional formations containing multiple programs, whereas programs can cross disciplinary boundaries. # Current Theories of Scientific Organization ## Logical structure and explanatory relations Hempel and Oppenheim treated scientific explanation as subsumption of the explanandum under general laws and initial conditions. The model made explicit the relation between explanans and explanandum, but its symmetry with prediction and dependence on laws proved too restrictive. It remains important because it establishes that explanation requires more than naming a target: a field must articulate relations that make the target expectable or intelligible (Hempel & Oppenheim, 1948). Subsequent accounts pluralized explanatory dependence. Kitcher emphasized unification through a small set of argument patterns; Salmon emphasized causal relevance and processes; Woodward linked causal explanation to invariance under interventions; and mechanists characterized mechanisms as organized entities and activities productive of regular changes (Kitcher, 1981; Salmon, 1984; Woodward, 2003; Machamer, Darden, & Craver, 2000). These theories disagree about explanation, which is evidence against treating one form - especially mechanism - as architecturally mandatory. ## Paradigms, research programs, and disciplinary matrices Kuhn\'s mature science is stabilized by shared exemplars, symbolic generalizations, models, and values rather than by a definition of subject matter alone. His later \'disciplinary matrix\' is especially relevant: a research community coordinates what problems are legitimate, what solutions look like, and what standards govern puzzle solving. Scientific revolutions can reorganize both ontology and explanatory targets (Kuhn, 1962/1970). Lakatos shifts the unit from paradigms to research programs with a relatively protected hard core and a changing protective belt; progress is judged by theoretical and empirical development over time (Lakatos, 1978). Neither account yields a universal list of objects, but both show that objects are stabilized inside structured practices. ## Experimental objects and epistemic things Hacking argues that scientific entities acquire special warrant through intervention and manipulation, not representation alone. Experimental practice can stabilize entities before theory converges (Hacking, 1983). Rheinberger\'s \'epistemic things\' are materially embodied targets whose relevant properties are not yet fully known; experimental systems generate differences that progressively articulate them (Rheinberger, 1997). Daston and Galison show that scientific objectivity itself has historical forms tied to representational practices and trained judgment (Daston & Galison, 2007). These approaches make instruments and representations constitutive of object stabilization without implying that instruments create every referent. ## Natural kinds, classifications, and constructed targets Essentialist natural kinds cannot organize all sciences. Biological species, psychiatric categories, social classifications, and computational types often have historical, functional, cluster-based, or engineered unity. Boyd\'s homeostatic property cluster account, Dupré\'s pluralism, and Hacking\'s analysis of interactive human kinds show that categories may be stable enough for inquiry without possessing classical essences (Boyd, 1991; Dupré, 1993; Hacking, 1999). Classification is therefore an epistemic achievement to be evaluated, not a universal discovery of fixed essences. ## Levels, mechanisms, and perspectival organization Marr distinguished computational, algorithmic, and implementational levels; explanatory questions change with level. Craver treats levels as component-mechanism relations rather than a single universal hierarchy. Wimsatt emphasizes robustness across independent means of detection and analysis. Giere\'s perspectivism and Cartwright\'s attention to capacities caution that models represent selected aspects under conditions, not complete mirrors of the world (Marr, 1982; Wimsatt, 2007; Craver, 2007; Giere, 2006; Cartwright, 1989). A general architecture must therefore include explicit units, levels, and scope conditions. ## Communities, boundaries, and institutional emergence Fleck described thought collectives and styles; Gieryn analyzed boundary work by which communities demarcate science; Abbott showed that disciplines organize through shifting oppositions and problem structures; and Stichweh connected differentiation to specialized communication and institutional reproduction (Fleck, 1935/1979; Gieryn, 1983; Abbott, 2001; Stichweh, 1992). These accounts explain disciplinary persistence and jurisdiction. They do not imply that communities may define arbitrary objects successfully: empirical resistance, technical performance, and cross-context reliability constrain stabilization. # Comparative Survey of Mature Disciplines Table 1 records dominant structures rather than exhaustive internal diversity. \'Observer\' identifies the epistemic role that selects and records evidence, not necessarily a person external to the system. \'Mechanism/dependency\' includes lawful, causal, structural, functional, historical, computational, interpretive, and statistical forms. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- **Discipline** **Primary object / **Explanandum** **Observer** **Unit of analysis** **Fundamental **Mechanism or **Characteristic **Evidence** **Typical domain** entities** dependency** questions** predictions** ---------------- ------------------- ------------------ ------------------------------------ ------------------------- ------------------ ---------------------- ------------------------ ------------------- ------------------- Physics Physical states, Events, systems, Experimental/theoretical System, particle, field, Fields, particles, Dynamical laws, Why does a state evolve; Measurement, Quantitative fields, spacetime, interactions, investigator with instruments ensemble, spacetime states, conservation, which invariants experiment, forecasts, matter-energy; distributions region observables, symmetry, constrain it? astronomical parameter observable symmetries causal/statistical observation, estimates, novel regularities evolution simulation effects Chemistry Substances, Transformation and Analytical/synthetic investigator Molecule, ion, reaction, Atoms, bonds, Energetic, kinetic, Why does a substance Spectroscopy, Products, rates, composition, stability of phase, material sample orbitals, structural, quantum, form/react; how does synthesis, assay, equilibria, structure, chemical systems molecules, phases reaction mechanisms structure determine crystallography, spectra, properties reactions, property? computation properties Biology Living systems, Organized Observer/experimenter across Gene, cell, organism, Organisms, cells, Mechanisms, selection, How is a trait produced, Experiment, Outcomes, heredity, persistence, laboratory and field lineage, population, genes, traits, inheritance, maintained, inherited, comparative data, distributions, development, variation, ecosystem by question populations development, function, or evolved? field observation, phylogenies, function, evolution adaptation, history sequencing, fossils functional effects lineage change Ecology Relations among Distribution, Field/lab/modeling observer within Individual, population, Organisms, Competition, Why are organisms Surveys, Population organisms and abundance, sampled systems community, ecosystem, populations, predation, mutualism, distributed thus; what experiments, remote trajectories, range environments across interaction, flux, landscape resources, dispersal, feedback, drives system change? sensing, models, shifts, community scales resilience habitats, flows disturbance long-term series responses Geology Earth materials, Present formations Field, laboratory, and remote Mineral, rock body, Minerals, rocks, Tectonics, erosion, How did this structure Outcrops, cores, Retrodictions, structures, and past observer stratum, fault, basin, fluids, landforms, deposition, form; what dating, geophysics, hazard processes, and events/processes tectonic plate plates metamorphism, process/history produced geochemistry, probabilities, history geochemical cycles it? models process consequences Astronomy Celestial objects, Observed signals Earth/space-based observer Photon event, object, Stars, planets, Gravity, radiation, What is this object; how Imaging, spectra, Transits, radiation, cosmic and inferred constrained to remote signals orbit, stellar galaxies, fields, fusion, accretion, did it form/evolve; what timing, surveys, positions, spectra, structures and cosmic processes population, cosmological matter, spacetime cosmological dynamics will be observable? gravitational event rates, evolution volume signals, simulation evolutionary states Linguistics Human language as Patterns in form, Analyst, speaker-judgment Feature, segment, Representations, Computation, What makes forms Corpora, Acceptability, structured meaning, participant, corpus/experimental morpheme, construction, categories, constraint, learning, possible; how are form elicitation, parsing, capacity, system, acquisition, observer utterance, discourse constructions, interaction, and meaning related? experiments, acquisition, use, and change variation, speakers, historical change typology, change, processing communities historical distribution comparison Psychology Behavior and mental Performance, Experimenter/clinician/participant Trial, response, person, Agents, Learning, memory, Why does behavior vary; Experiments, tests, Response processes at experience, observer task, group, representations, perception, decision, which processes generate observation, distributions, individual and learning, developmental trajectory processes, traits, motivation, social it? reports, performance, group levels cognition, affect, situations influence physiology, intervention development longitudinal data effects Sociology Social relations, Patterns of Researcher often embedded in or Actor, tie, role, group, Actors, networks, Interaction, How are patterns Surveys, Associations, institutions, coordination, reflexive toward social systems institution, population, norms, socialization, power, produced/reproduced; why administrative trajectories, groups, structures, inequality, event organizations, diffusion, selection, do institutions change? data, ethnography, diffusion, policy and change organization, categories institutionalization experiments, or institutional diffusion networks effects Anthropology Humans in cultural, Meaningful Participant-observer, comparative Practice, person, Persons, symbols, Meaning, exchange, How do practices become Ethnography, Contextual social, biological, practices, analyst, laboratory investigator household, community, practices, kinship, learning, meaningful and durable; archaeology, expectations, and historical lifeways, material artifact, population institutions, adaptation, historical how do populations vary? comparison, historical variation and biological bodies, material formation biological reconstructions, variation culture measures, archives pattern contrasts Economics Allocation, Choices, prices, Analyst using observational, Decision, agent, market, Agents, Optimization, How do Natural/field/lab Comparative production, distributions, experimental, administrative data firm, household, economy preferences, equilibrium, strategic constraints/incentives experiments, panel statics, causal exchange, growth, strategic technologies, interaction, learning, generate outcomes; data, models, effects, market and incentives, outcomes goods, causal response effects of national accounts macro trajectories institutions, institutions, interventions? aggregate dynamics expectations Computer Science Computation, Computability, Designer, analyst, verifier, Operation, algorithm, Symbols, states, Computation, What can be computed; Proof, benchmark, Outputs, resource information correctness, experimenter program, machine, programs, transformation, with what resources; simulation, bounds, processes, complexity, protocol, data structure machines, data, communication, does a system satisfy a testing, formal correctness, algorithms, behavior of agents learning, control specification? verification performance, artificial systems constructed failure modes systems Information Creation, Information Analyst of users, documents, Document, record, query, Documents, data, Representation, How is information Logs, retrieval Retrieval Science representation, behavior and infrastructures, metrics user episode, collection, metadata, users, indexing, retrieval, organized, found, tests, performance, organization, performance of network systems, communication, interpreted, and used? bibliometrics, user diffusion, use, retrieval, use, and informational institutions relevance judgment studies, relevance, citation flow of information systems ethnography patterns Cybernetics Control and Regulation, Observer-controller whose boundary State variable, loop, Systems, signals, Feedback, feedforward, How is stability System Stability, communication in stability, may be inside the system controller, system, goals, requisite variety, achieved under identification, response, animals, machines, adaptation, message disturbances, adaptation disturbance; how does simulation, convergence, and organizations feedback channels information guide experiments, oscillation, control? operational traces controllability Systems Theory Organization and Cross-domain Modeler selecting system boundaries Component, relation, Components, Interaction, feedback, Which organizational Models, System regimes, behavior of wholes patterns of and levels subsystem, network, whole relations, emergence, constraint, properties recur; how do simulations, robustness, and organization, boundaries, flows, self-organization parts generate whole comparative cases, propagation, interdependencies emergence, and hierarchies behavior? network and emergent patterns dynamics dynamical data Cognitive Cognition across Perception, Interdisciplinary investigator using Representation/process, Agents, Computation, neural How is intelligent Behavioral Performance, Science computational, reasoning, converging methods task episode, neural representations, dynamics, learning, behavior generated experiments, errors, neural, behavioral, learning, circuit, neural systems, embodiment, across levels? neuroscience, neural/behavioral embodied, and language, action, agent-environment system bodies, artifacts distribution modeling, dynamics, transfer social levels representation linguistics, AI Human Factors Human performance Fit among human Analyst/designer observing Operator action, task, People, tasks, Workload, Why does performance Experiments, field Performance, and safety in capabilities, operational work team, workstation, tools, perception-action, succeed/fail; how do studies, incident workload, errors, designed tasks, technology, sociotechnical episode organizations, coordination, error, design and organization records, reliability, safety sociotechnical and environment hazards resilience shape it? simulation, task outcomes systems analysis Human-Computer Human use and Coupled behavior, Researcher/designer; users may be Action/event, task People, artifacts, Perception-action, How do people and Experiments, logs, Performance, Interaction experience of usability, participants and interpreters episode, interaction representations, cognition, feedback, systems mutually shape field studies, adoption, errors, interactive experience, sequence, practice, tasks, practices, learning, action and experience? interviews, experience, computational appropriation, community institutions coordination, prototypes, breakdown, transfer systems sociotechnical meaning-making analytics effects --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- # Recurring Architectural Structures The survey converges, but not on the candidate inventory in its original form. Object, observer, observation, relationship, mechanism, representation, explanation, prediction, and evidence are not equally fundamental. \'Object\' is often plural or processual; \'observer\' is sometimes distributed or endogenous; \'mechanism\' is one explanatory form among several; and \'prediction\' may be replaced by retrodiction, constraint, classification, proof, intervention, or qualitative expectation. The stable commonality is functional. ----------------------------------------------------------------------- **Component** **Function** ----------------------------------- ----------------------------------- 1\. Phenomenal domain and A field identifies repeatable or explanatory targets historically traceable phenomena, patterns, capacities, events, or problem classes for which descriptions alone are insufficient. The target need not be a single entity. 2\. Units, levels, boundaries, and Inquiry specifies what counts as a scope case, at which scale or level it is analyzed, where the system boundary lies, and under which conditions claims apply. 3\. Ontological commitments The field identifies relevant entities, properties, relations, processes, structures, or constructed types. Commitments may be realist, instrumental, perspectival, or pluralist, but cannot remain entirely implicit. 4\. Epistemic access The field establishes operations by which claims become answerable: observation, measurement, instrumentation, experimentation, intervention, records, comparison, proof, simulation, testimony, or field participation. 5\. Public representation The field stabilizes targets and dependencies through shareable representations: taxonomies, equations, diagrams, maps, models, narratives, code, datasets, specimens, and simulations. 6\. Explanatory dependencies The field states what makes a difference to the target. Forms include laws, causes, mechanisms, constraints, functions, computations, structures, equilibria, selection processes, histories, meanings, and statistical relations. 7\. Success and error constraints Claims face standards that can reveal failure: empirical fit, reproducibility, robustness, intervention, predictive or retrodictive accuracy, proof, unification, coherence, external validity, and comparative explanatory gain. Stabilizing envelope: research Exemplars, trained judgment, practice instruments, repositories, standards, institutions, and communities preserve and revise the seven functions. This envelope explains disciplinary durability; it is not itself the explanans in every study. ----------------------------------------------------------------------- The architecture can be expressed compactly. A scientific research formation stabilizes a target T when a community can (a) individuate instances of T at specified units and levels, (b) obtain disciplined epistemic access to them, (c) represent their relevant features publicly, (d) propose dependencies that answer contrastive explanatory questions, and (e) expose those claims to shared error-detection and comparison. Ontology, method, and representation are mutually constraining rather than linearly ordered. # Counterexamples ## Method-centered fields Statistics, microscopy, spectroscopy, and parts of computer science appear organized around methods rather than natural objects. They do not refute the architecture because their explanatory targets are problem classes - uncertainty, inference, detection, computation, or measurement - and their objects are often formal or constructed. They do refute the claim that every discipline requires one bounded natural kind. ## Historical sciences Geology, evolutionary biology, cosmology, archaeology, and historical linguistics often explain singular or path-dependent outcomes. Their strongest achievements may be retrodictive consilience, constraint of possible histories, and risky traces expected under one history but not another. They refute prediction symmetry as a universal criterion, not the need for success constraints. ## Interpretive and reflexive sciences Anthropology, sociology, and parts of linguistics investigate agents whose classifications and interpretations can alter the phenomena. Hacking\'s interactive kinds and reflexive methodology show that the observer-observed relation cannot always be externalized. These fields still establish units, evidence, representations, dependencies, and criticism, but explanation may include reasons, meanings, institutions, and looping effects alongside causes. ## Formal and design sciences Mathematics and theoretical computer science prove consequences within formal systems; design sciences study artificial systems partly by constructing them. Their evidence includes proof and artifact performance, which differ from observation of unaided nature. Simon\'s sciences of the artificial show that purpose, specification, and synthesis can be legitimate explanatory contexts. These cases require \'epistemic access\' and \'success constraints\' broad enough to include proof, verification, and constructive demonstration. ## Fields without a single paradigm Psychology, sociology, anthropology, HCI, and cognitive science contain multiple ontologies and explanatory traditions. They remain disciplines because institutional and problem continuity can coexist with theoretical pluralism. Kuhnian consensus is therefore a degree of maturation within programs, not a necessary global state for an entire discipline. # Proposed General Architecture No accepted philosophy-of-science theory currently specifies how all sciences define their objects. Existing accounts explain different dimensions: logical relations, causal dependence, mechanisms, unification, paradigms, research programs, experimental manipulation, classification, perspectival representation, and community formation. The present proposal is therefore a comparative synthesis, not a discovered consensus theory. ## Definitions ----------------------------------------------------------------------- **Term** **Definition** ----------------------------------- ----------------------------------- Scientific object A relatively stable target of systematic inquiry, individuated through coordinated ontological, epistemic, and representational practices, about which intersubjective claims can be made. Explanatory target The event, pattern, capacity, regularity, outcome, or contrast for which understanding is sought. Unit of analysis The smallest or principal case treated as one instance for a particular inquiry; units may differ across levels. Epistemic access The disciplined operations through which evidence relevant to a target is generated, preserved, or evaluated. Representation A public structure used to classify, measure, model, simulate, prove, or communicate selected features of a target. Explanatory dependency A relation in virtue of which variation, occurrence, organization, or possibility of an explanatory target becomes intelligible. Success constraint A standard capable of discriminating stronger from weaker claims and exposing error. Discipline A durable social organization of research containing objects, questions, methods, standards, exemplars, and institutions; it need not map one-to-one onto an object. ----------------------------------------------------------------------- ## Relations among components 1. Target selection is theory-laden but empirically constrained. Phenomena become salient against prior questions and representations, yet recalcitrant observations can force reclassification. 2. Units and boundaries mediate ontology. The same domain can support genes, organisms, populations, or ecosystems as units without one eliminating the others. 3. Epistemic access co-produces object stability. Instruments, records, and interventions determine which properties can be reliably discriminated, while successful manipulation and robustness can increase realist warrant. 4. Representations make comparison possible but are not identical with their targets. Multiple representations may be equivalent for one purpose and incompatible for another. 5. Explanatory dependencies answer contrastive questions under scope conditions. No universal dependency type is privileged across all sciences. 6. Success constraints close the loop by selecting, revising, or rejecting ontologies, measurements, representations, and explanations. 7. Communities stabilize the loop through shared practices, but stabilization remains provisional because standards, instruments, and targets can change. ## Necessary and non-necessary components ----------------------------------------------------------------------- **Candidate** **Status** **Reason** ----------------------- ----------------------- ----------------------- Object Retained, generalized Required as a stable target, but may be a process, relation, problem class, formal structure, or constructed system rather than a natural entity. Observer Not a core component Always practically present, but its location and role vary; better represented through epistemic access and reflexivity. Observation Retained, generalized Observation alone excludes proof, records, simulation, and intervention; replaced by epistemic access. Relationship Absorbed Relations are part of ontology and explanatory dependency. Mechanism Not universal Central in many sciences, absent or secondary in lawful, structural, historical, interpretive, and formal explanation. Representation Retained Required for public, reproducible comparison, though not necessarily pictorial or symbolic in one fixed form. Explanation Retained as function The architecture concerns explanatory organization, but permits plural explanatory forms. Prediction Not universal Replaced by broader success constraints including retrodiction, intervention, proof, and unification. Evidence Retained within Evidence is epistemic access and indispensable, but its success constraints forms and standards differ. ----------------------------------------------------------------------- # Application to Interaction as a Worked Example Interaction is examined only after the architecture has been derived. The exercise asks whether it can be organized as a scientific target, not whether it warrants a dedicated discipline or whether any existing ontology is correct. ---------------------------------------------------------------------------- **Architecture **Possible realization for **Assessment** component** interaction** ----------------------- ---------------------------- ----------------------- Phenomenal domain / Reciprocal or sequential Compatible, but targets changes among coupled boundaries between agents, artifacts, interaction, action, representations, and communication, control, environments; coordination, and activity must be breakdown, adaptation, explicit. transfer, and emergent trajectories. Units / levels Event, action-response pair, Compatible, but no state transition, episode, uniquely privileged task, practice, smallest unit has been relationship, team, established across institution, or longitudinal contexts. trajectory. Ontology Participants or agents, Existing vocabularies environment, states, largely suffice; actions, signals or proposed entities representations, remain theory-dependent opportunities/constraints, and should not be histories, and coupling treated as proven relations. universals. Epistemic access Event logs, observation, Strong compatibility; experiments, interviews, measurement validity physiological measures, and context loss are field records, trace major risks. reconstruction, intervention, and simulation. Representation State-transition models, Strong plurality; interaction sequences, representation graphs, grammars, task equivalence is an open models, activity systems, empirical and formal dynamical systems, question. computational simulations. Explanatory Feedback, affordances, Many candidate dependencies information constraints, mechanisms already cognition, learning, habit, belong to adjacent coordination, social norms, sciences; institutional rules, interaction-level semantics, and technical autonomy is unproven. behavior. Success constraints Cross-context prediction, Compatible; decisive retrodiction of breakdown, tests require intervention effects, comparison with transfer, model comparison, integrated invariance, and explanatory existing-theory compression beyond baselines. component-only accounts. ---------------------------------------------------------------------------- The worked example establishes structural compatibility only. Interaction can be individuated as a family of explanatory targets, observed through multiple methods, represented formally, and related to candidate dependencies. However, these conditions are permissive: many legitimate research objects satisfy them while remaining shared across disciplines. To establish theoretical independence, an interaction-centered program would need to show stable interaction-level variables or invariants that produce explanatory and predictive gains not obtainable by integrating cognitive, ecological, informational, social, control, and computational accounts. A falsifying result would be equally clear: if every robust interaction phenomenon can be explained without residual loss by existing component and relational theories, and if proposed interaction-level constructs add no comparative prediction, intervention guidance, or unification, interaction remains a cross-disciplinary object rather than an autonomous theoretical domain. # Threats to Validity - Selection bias: eighteen fields cannot represent every science. Medicine, mathematics, statistics, climate science, neuroscience, archaeology, and engineering could shift emphasis, although the counterexample analysis incorporates several of their organizational forms. - Internal heterogeneity: each table entry compresses contested subfields. The architecture is intended to describe recurring functions, not adjudicate each discipline\'s ontology. - Presentist reconstruction: contemporary disciplinary structures may conceal historical alternatives. Kuhnian and historical work partly corrects this, but the survey is not a full genealogy. - Philosophical underdetermination: realism, instrumentalism, perspectivism, and social constructivism permit different interpretations of stabilization. The framework is designed to remain neutral where the comparative result does not require resolution. - Functional abstraction: the seven components may appear inevitable because they are broadly formulated. Their value depends on discriminating what is not universal - single objects, mechanisms, external observers, experiments, and prediction - and on specifying relations among the retained functions. - Application contamination: prior interest in interaction could bias the derived framework. The architecture was therefore formulated and tested against the full disciplinary sample before interaction was evaluated. - Evidence asymmetry: foundational philosophy sources are not a systematic bibliometric sample. The paper reviews influential competing positions and records disagreement rather than claiming exhaustive consensus. # Discussion The central result is a qualified convergence. Mature disciplines do not determine their primary objects by discovering a single metaphysically given partition of reality. Nor are objects merely arbitrary products of communities. They are stabilized through a recurrent coupling of explanatory demand, ontological articulation, epistemic access, public representation, and error-sensitive comparison. This coupling can converge on entities such as electrons, processes such as evolution, relations such as ecological interaction, formal structures such as algorithms, or historically constituted practices. The primary object of a discipline is therefore best understood as a stabilized explanatory target system rather than a noun. \'System\' here does not imply systems theory; it denotes the linked set of targets, units, ontological commitments, access procedures, representations, dependencies, and standards that make sustained inquiry possible. A discipline may host several such systems, and one system may cross disciplinary boundaries. The distinction between object and discipline resolves apparent anomalies. Cognition is studied by psychology, neuroscience, linguistics, computer science, anthropology, and cognitive science. Information is studied in physics, biology, computer science, communication, and information science. Interaction similarly may be a primary object of particular research programs without being the exclusive object of HCI or the basis of an independent discipline. Disciplinary autonomy requires additional sociological and theoretical conditions: a sustained problem agenda, specialist training, institutions, journals, instruments or datasets, and demonstrable explanatory gains. The architecture also reframes scientific emergence. New sciences are not born when a label is coined. They emerge when previously dispersed anomalies or questions become a coherent target domain; units and boundaries become reproducible; ontologies support cumulative models; epistemic techniques make relevant differences detectable; explanations outperform competitors; and a community preserves the resulting standards. Instruments and communities can lead this process, but they cannot substitute indefinitely for explanatory success. No single philosophical account is sufficient. Hempel clarifies the explanandum-explanans relation; Kuhn and Lakatos explain organized continuity and change; Hacking and Rheinberger explain experimental stabilization; natural-kind debates explain classificatory pluralism; mechanism and intervention accounts explain difference-making in many empirical sciences; unification accounts explain cross-domain compression; and sociology of science explains institutional persistence. The proposed architecture is the intersection of these contributions after counterexamples remove non-universal requirements. # Conclusion Yes, there is a general architecture by which mature sciences define and organize primary objects of explanation, but it is not a universal object ontology or a single theory of explanation. Mature sciences recurrently coordinate seven functions: a phenomenal domain and explanatory targets; units, levels, boundaries, and scope; ontological commitments; epistemic access; public representations; explanatory dependencies; and success and error constraints. Research communities, instruments, exemplars, and institutions stabilize this architecture over time. The architecture is minimal because removing any retained function prevents cumulative explanatory inquiry: without targets there is no explanandum; without units and scope claims cannot be compared; without ontology relevant differences are unspecified; without epistemic access claims cannot answer to evidence; without representations they cannot circulate or accumulate; without dependencies description does not become explanation; and without success constraints error cannot be discriminated from progress. Conversely, a single natural object, an external observer, experimental manipulation, mechanism, and novel prediction are not universal requirements. Interaction is structurally compatible with this architecture. That result supports treating interaction as a possible primary object of particular scientific explanations. It does not establish that interaction is theoretically autonomous, that one ontology is correct, or that a dedicated discipline is justified. Those stronger conclusions require comparative explanatory gains that have not been demonstrated by structural analysis alone. # References Abbott, A. (2001). Chaos of disciplines. University of Chicago Press. Bertalanffy, L. von. (1968). General system theory. George Braziller. Boyd, R. (1991). Realism, anti-foundationalism and the enthusiasm for natural kinds. Philosophical Studies, 61, 127-148. Card, S. K., Moran, T. P., & Newell, A. (1983). The psychology of human-computer interaction. Erlbaum. Cartwright, N. (1983). How the laws of physics lie. Oxford University Press. Cartwright, N. (1989). Nature\'s capacities and their measurement. Oxford University Press. Craver, C. F. (2007). Explaining the brain. Oxford University Press. Daston, L. (Ed.). (2000). Biographies of scientific objects. University of Chicago Press. Daston, L., & Galison, P. (2007). Objectivity. Zone Books. Dupré, J. (1993). The disorder of things. Harvard University Press. Fleck, L. (1979). Genesis and development of a scientific fact (original work published 1935). University of Chicago Press. Gibson, J. J. (1979). The ecological approach to visual perception. Houghton Mifflin. Giere, R. N. (2006). Scientific perspectivism. University of Chicago Press. Gieryn, T. F. (1983). Boundary-work and the demarcation of science from non-science. American Sociological Review, 48, 781-795. Hacking, I. (1983). Representing and intervening. Cambridge University Press. Hacking, I. (1999). The social construction of what? Harvard University Press. Hempel, C. G., & Oppenheim, P. (1948). Studies in the logic of explanation. Philosophy of Science, 15, 135-175. Hutchins, E. (1995). Cognition in the wild. MIT Press. Kitcher, P. (1981). Explanatory unification. Philosophy of Science, 48, 507-531. Kuhn, T. S. (1970). The structure of scientific revolutions (2nd ed.; original work published 1962). University of Chicago Press. Lakatos, I. (1978). The methodology of scientific research programmes. Cambridge University Press. Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67, 1-25. Marr, D. (1982). Vision. W. H. Freeman. Mayr, E. (1982). The growth of biological thought. Harvard University Press. Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19, 113-126. Norman, D. A. (2013). The design of everyday things (rev. ed.). Basic Books. Pearl, J. (2000). Causality. Cambridge University Press. Popper, K. R. (1959). The logic of scientific discovery. Hutchinson. Rheinberger, H.-J. (1997). Toward a history of epistemic things. Stanford University Press. Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton University Press. Simon, H. A. (1996). The sciences of the artificial (3rd ed.). MIT Press. Stichweh, R. (1992). The sociology of scientific disciplines. Science in Context, 5, 3-15. Suchman, L. A. (1987). Plans and situated actions. Cambridge University Press. Wiener, N. (1948). Cybernetics. MIT Press. Wimsatt, W. C. (2007). Re-engineering philosophy for limited beings. Harvard University Press. Woodward, J. (2003). Making things happen. Oxford University Press. # Appendix A: Evaluation Criteria for a Candidate Scientific Object ----------------------------------------------------------------------- **Criterion** **Question** **Failure condition** ----------------------- ----------------------- ----------------------- Target stability Can researchers Cases cannot be identify sufficiently individuated except by comparable instances or conclusions the theory traces? is meant to establish. Unit and scope Are units, levels, Claims shift units or boundaries, and boundaries conditions explicit? opportunistically. Ontological clarity Are relevant entities, Terms remain properties, relations, metaphorical or or processes collapse into distinguished? neighboring concepts. Epistemic access Can evidence be No reproducible route generated or recovered connects claims to by disciplined observations, records, procedures? proofs, or interventions. Representation Can targets and Representations are dependencies be private, unstable, or publicly encoded and inseparable from one compared? implementation without justification. Explanatory dependence Does the account It merely redescribes specify what makes a or labels observations. difference and why? Error sensitivity Could evidence No conceivable outcome discriminate the weakens the claim. account from alternatives? Comparative gain Does the Existing integrated object-centered theories perform organization improve equally with fewer prediction, assumptions. retrodiction, intervention, unification, or understanding? ----------------------------------------------------------------------- ======================================================================== ## FILE: docs/02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.md (1058 lines, 54.0 KiB) ======================================================================== Formal research paper July 2026 ----------------------------------------------------------------------- **Final determination: 3. A general theory of projection is justified, but semantic invariance requires strict scope conditions.** ----------------------------------------------------------------------- ----------------------------------------------------------------------- # Abstract Representation is not one homogeneous relation. Across semiotics, philosophy of science, mathematics, logic, cognitive science, cartography, information visualization, programming languages, databases, compilers, accessibility, and human-computer interaction, a representation is treated variously as a sign relation, a model, a structure-preserving mapping, an encoding, an external cognitive resource, an abstraction, a view, or a public instrument. No single definition subsumes these traditions without loss. A stable cross-disciplinary core nevertheless emerges: a representation is a materially or formally realized vehicle used within an interpretive practice to provide selective access to a declared target under a mapping or rule of correspondence. Representations preserve some relations and observables, transform others, omit others, and introduce operations, saliences, ambiguities, and costs. Equivalence is therefore typed rather than absolute. Syntactic, semantic, informational, structural, topological, computational, inferential, task, perceptual, behavioral, and interactional equivalence impose different identity conditions and require explicit observers, contexts, metrics, and tolerances. The paper evaluates whether \'projection\' adds explanatory value beyond representation. Existing theories supply most component mechanisms: model morphisms, abstraction functions, database views, bidirectional lenses, encodings, simulations, and scientific models. They do not provide one shared contract linking preservation and loss to epistemic access and action opportunity across formal and empirical domains. Projection is therefore justified as a cross-disciplinary analytical role, not as a new primitive substance: a declared transformation from a target description to a representation form for specified observers and uses. Semantic invariance is coherent only when the target content, interpretation rules, admissible contexts, observables, and tolerance are fixed. Informational equivalence does not imply inferential, perceptual, task, behavioral, or interactional equivalence. The resulting reusable artifacts are a representation taxonomy, typed equivalence matrix, projection contract, comparison protocol, and falsification matrix. Primary contribution: representation change can be analyzed rigorously by declaring a target, mapping, preservation profile, loss profile, operations, observer model, use conditions, and failure conditions; no unqualified semantic-invariance claim is scientifically defensible. # 1. Problem Statement Scientific and computational work depends on representations while repeatedly warning that representations are not their targets. Equations, diagrams, data tables, maps, simulations, source code, database views, interfaces, and narratives can concern the same target yet support different inferences and actions. The central problem is not merely that formats differ. It is that every representation selects structure, establishes observables, redistributes cognitive work, and constrains what can be inspected or changed. Three errors follow from treating representation as transparent. First, identity is inferred from common reference: two vehicles are assumed equivalent because they concern the same target. Second, meaning is inferred from information preservation: equal recoverable data are assumed to yield equal understanding. Third, behavior is attributed directly to representation without specifying observers, tasks, prior knowledge, context, or available operations. This paper rejects all three inferences. The research question is: What is a representation, what can remain invariant across representations, and what changes when the same underlying target is represented differently? The inquiry is independent of specific interfaces and software architectures. It asks whether existing theories are sufficient or whether a general theory of projection is required to coordinate them. # 2. Literature Review Method The review uses a structured conceptual synthesis rather than a statistical meta-analysis. It samples foundational and primary work from philosophy of science and language, semiotics, formal logic, mathematics, scientific modeling, information theory, cognitive science, distributed and external cognition, visualization, cartography, programming-language semantics, compilers, databases, knowledge representation, accessibility, and HCI. Sources were selected when they explicitly define representation, specify a mapping or interpretation relation, characterize preservation or loss, define an equivalence relation, or report effects of representational form on reasoning and action. Claims were coded along eight dimensions: vehicle, target, mapping, interpreter, preserved properties, transformed or omitted properties, available operations, and evaluation criterion. Contradictory positions were retained. The synthesis does not use a pre-existing interaction ontology as evidence. It distinguishes observations reported in empirical studies from philosophical interpretation and from the paper\'s proposed analytical framework. Limitations are material. Several traditions use the same word for different roles, while others avoid the word but formalize related structures. Formal results establish properties relative to stipulated semantics and observables; they do not automatically generalize to human interpretation. Empirical results establish performance effects under specific tasks and populations; they do not prove universal representational mechanisms. # 3. Major Theories of Representation ## 3.1 Semiotic and referential accounts Peircean semiotics treats a sign through a triadic relation among sign, object, and interpretant. Signhood is relational rather than an intrinsic property of a vehicle. This blocks a target-only definition: a mark is not a representation merely by resembling or correlating with something; it functions representationally through an interpretive relation. Saussurean traditions emphasize differences within a sign system and conventional relations between signifier and signified. Goodman rejects resemblance as a necessary basis of representation and analyzes symbol systems through reference, denotation, exemplification, and syntactic and semantic differentiation. Strength: these accounts explain why identical vehicles may mean differently across practices and why dissimilar vehicles may represent the same target. Limit: they offer limited quantitative guidance about preserved structure, computational behavior, or task performance. Their central constraint is indispensable: representation requires a rule-governed relation, not mere physical similarity. ## 3.2 Philosophy of science and scientific modeling Scientific-representation theories disagree over whether representation is resemblance, isomorphism, partial isomorphism, similarity, inference, or use. Structural accounts emphasize mappings between model structure and target structure. Similarity accounts make representation selective and purpose-relative. Inferential conceptions emphasize a model\'s capacity to license competent reasoning about a target. Pragmatic accounts place agents, purposes, and contexts inside the representation relation. Perspectival approaches stress that scientific representations disclose selected aspects under conditions rather than mirror complete reality. A common result is negative: no representation represents everything about its target. Scientific models idealize, abstract, distort, and sometimes deliberately misrepresent while remaining epistemically useful. Accuracy is multidimensional and purpose-relative, but not arbitrary; empirical fit, robustness, inferential reliability, and error characterization constrain acceptable use. ## 3.3 Mental, external, and distributed representation Cognitive science uses \'representation\' for internal states or structures that carry content and participate in computation, but representationalism is contested by ecological, enactive, and dynamical approaches. External-cognition research shifts attention from internal content to the joint system formed by agents and external structures. Zhang and Norman\'s representational analysis shows that formally equivalent task structures can distribute information differently between mind and environment, changing memory demands and permissible operations. Hutchins extends the unit to socially and materially distributed cognitive systems. Strength: these traditions explain why a vehicle can reorganize reasoning without changing target information. Limit: claims about internal representations remain theoretically disputed, and external performance effects depend on learned conventions, perceptual capacities, and task structure. ## 3.4 Mathematics, logic, and model theory Mathematics supplies precise preservation vocabulary. A homomorphism preserves specified operations or relations; an isomorphism is a structure-preserving bijection with an inverse of the relevant kind; homeomorphism preserves topological structure; equivalence relations partition objects under declared criteria. Model theory distinguishes a formal language, a structure interpreting it, and satisfaction. Logical equivalence concerns truth across interpretations; elementary equivalence concerns satisfaction of the same first-order sentences; definitional and categorical equivalences impose different translations between theories. These results establish that invariance is always indexed to structure. Isomorphic objects may differ physically; homeomorphic spaces may differ metrically; logically equivalent expressions may differ cognitively or computationally. Formal equivalence cannot be transferred across levels without proof. ## 3.5 Information theory and coding Information theory formalizes uncertainty reduction, channel capacity, coding, and loss without supplying semantic meaning. Shannon explicitly brackets semantic aspects of communication from the engineering problem. Lossless coding permits exact reconstruction of a source sequence under a code; lossy coding permits controlled distortion under a measure. Sufficient statistics preserve all information in a sample relevant to a specified parameter, demonstrating again that preservation is relative to an inferential target. Strength: exact measures of recoverability, uncertainty, and distortion. Limit: identical information-theoretic content can support different interpretations, inferences, and actions. Semantic or behavioral equivalence cannot be inferred from entropy or decodability alone. ## 3.6 Cartography and information visualization Cartography treats projection explicitly as a mapping from one geometric surface to another. No flat world map preserves area, angle, shape, direction, and distance globally. Projection families declare which properties are preserved and where distortion occurs. Visualization similarly encodes data attributes into graphical marks and channels. Graphical-perception experiments show that encodings differ in decoding accuracy; position along a common scale generally supports more accurate quantitative judgment than area or volume. A visualization may therefore be data-correct while inferentially poor. These fields provide the clearest empirical analogy for a projection contract: source domain, target form, invariant class, distortion class, and intended use must be stated together. ## 3.7 Programming languages, compilers, and computation Programming-language semantics distinguishes syntax from denotation, operational behavior, and observations. Two programs may be syntactically different yet denotationally equivalent, contextually equivalent, or bisimilar under defined observations. Compiler correctness is commonly expressed as preservation of semantics or observable behavior from source to target, with explicit allowances for undefined behavior, resource variation, and implementation-specific observations. Abstract interpretation formalizes sound approximation between concrete and abstract semantic domains, often through Galois connections. Soundness preserves truth of specified properties from abstraction to concrete behavior; completeness is stronger and frequently unavailable. This is a mature theory of projection-like mapping, but its scope is formal semantic analysis rather than human epistemic access. ## 3.8 Databases, views, and bidirectional transformations Codd\'s relational model separates logical data structure from physical representation and motivates data independence. A database view exposes a derived representation of source data. View-update theory asks how changes to the view correspond to changes in the source. Bidirectional transformations and lenses formalize paired mappings subject to round-trip laws. These theories demonstrate that projection is not only read access: available updates and their consistency conditions are part of the representational relation. Limit: database equivalence normally presumes formal schemas and well-defined queries. It does not explain salience, discoverability, perceptual interpretation, or learned action strategies. ## 3.9 Knowledge representation Knowledge representation treats formal languages as surrogates for domains, commitments about what exists, fragments of reasoning, media for computation, and means of human expression. Ontologies, description logics, frames, semantic networks, and probabilistic models preserve different inferential commitments. Expressiveness trades off against tractability and decidability. Two formalisms may encode corresponding facts yet differ in what can be inferred efficiently or transparently. ## 3.10 Accessibility, multimodality, and HCI Accessibility standards distinguish content and relationships from sensory presentation. Requirements not to depend solely on color, shape, location, or sound imply that a target instruction or relation should survive modality change. Yet modality substitution is not identity: spatial overview, temporal scanning, privacy, precision, fatigue, and learnability can differ. HCI adds mappings, feedback, signifiers, constraints, and action availability. Interface forms are therefore not passive displays of an invariant semantics; they mediate observation and intervention. # 4. Representation-Target Relations A representation cannot be adequately defined by a vehicle alone. The minimum relation includes a vehicle V, a target T, a correspondence or construction rule M, an interpretive practice I, and a use context C. The target need not be physical reality. It may be a scientific object, dataset, formal structure, process, model, possible state, rule system, or prior representation. Nor must the target be fully determinate independent of practice: classifications and model-defined quantities may be partly constituted by the representational framework. The paper adopts the following neutral definition: A representation is a materially or formally realized vehicle that, within an interpretive practice, provides selective access to a declared target by means of a rule-governed correspondence. \'Selective access\' covers reference, measurement, inference, simulation, communication, coordination, and intervention. The definition does not require resemblance, mental content, full fidelity, or observer-independent semantics. Meaning, content, information, and interpretation remain distinct. Information concerns distinctions and recoverability under a code or probability model. Content is what a representation is taken to be about or to assert under a semantics. Meaning includes inferential, pragmatic, or use consequences within an interpretive system. Interpretation is the process or rule by which a vehicle is related to content or target. A single information-bearing pattern can receive multiple interpretations; a common content can be encoded with different information costs. # 5. Preservation, Transformation, and Loss Representation is selective preservation under transformation. Preservation claims identify a relation or observable P such that relevant distinctions in the target remain recoverable or valid in the representation. Transformation claims identify systematic changes to form, scale, granularity, coordinate system, ordering, or dynamics. Omission claims identify target distinctions not encoded or not recoverable. Introduction claims identify structure contributed by the representation, including categories, visual grouping, defaults, coordinate axes, interaction operations, or uncertainty not present in the target description. -------------------------------------------------------------------------------- **Property** **Meaning of **Typical test** **Failure preservation** example** ----------------- ----------------- -------------------------- ----------------- Identity Declared target Injectivity or stable Aggregation entities remain identifiers under scope. merges distinct distinguishable entities. under the mapping. Semantic Declared Interpret both forms under A label relations propositions or a common semantics. translation reference changes category relations retain boundaries. truth conditions. Structure Specified Homomorphism/isomorphism A table omits relations and test. graph operations reachability commute with the structure. mapping. Topology Continuity, Homeomorphism or adjacency Map projection adjacency, or comparison. tears or changes neighborhood is neighborhood. retained. Order Ordering Monotonicity/order Alphabetical relations remain isomorphism. sorting destroys valid. temporal sequence. Quantity Specified Metric error bounds. Area encoding measures remain biases magnitude accurate within estimates. tolerance. Temporal Ordering, Trace or temporal-logic Narrative structure duration, or comparison. linearizes simultaneity is concurrent preserved. events. Uncertainty Probability, Calibration and Point estimate interval, propagation tests. suppresses provenance, or distribution. confidence is retained. Constraints Valid and invalid Constraint satisfaction or View admits states/actions round-trip tests. updates with no remain valid source correspondingly update. represented. Computational Declared Contextual equivalence, Optimization behavior observations of bisimulation, refinement. changes execution remain floating-point the same. results. Inferential Queries or Theory interpretation or Abstraction consequences conclusions in a query equivalence. proves only a declared logic strict subset. are preserved. Action Specified Operation-set and Read-only view possibilities feasible transition comparison. removes update operations and capability. effects correspond. -------------------------------------------------------------------------------- Loss cannot generally be measured independently of purpose and observer. Information-theoretic loss requires a source distribution and distortion measure. Structural loss requires a declared signature. Semantic loss requires an interpretation. Task loss requires a performance criterion. Perceptual loss requires an observer model. A purpose-independent catalogue of omitted distinctions is possible, but assigning importance to those omissions is not. # 6. Typed Equivalence Relations \'Equivalent\' is scientifically incomplete unless the equivalence type, observables, context, and tolerance are stated. The following matrix distinguishes relations that are often conflated. ---------------------------------------------------------------------------------------------------- **Type** **Must remain the same** **May differ** **Test / scope condition** ----------------- ---------------------------------- ----------------- ----------------------------- Syntactic Form under a grammar or Meaning, Token/tree equality or normalization rule. behavior, use. canonicalization. Semantic Denotation or truth conditions Syntax, cost, Interpretation equality over under a declared semantics. salience, specified models. interaction. Informational Recoverable distinctions or mutual Presentation, Lossless transforms or reconstructability. inference cost, bounded information loss. behavior. Structural Selected relations and operations. Unselected Homomorphism/isomorphism over properties and a signature. material realization. Topological Continuity and neighborhood Metric, angle, Homeomorphism or relations. area, scale. topology-preserving map. Computational Declared observable execution Internal steps, Contextual equivalence, behavior. resources, bisimulation, refinement. syntax. Inferential Answers or consequences for a Other Query equivalence or specified query/logic class. consequences, consequence preservation. cognitive cost. Task Success distribution for a Strategies, time, Equivalence/non-inferiority specified task and population. errors outside with tolerance. metric. Perceptual Discriminability or perceptual Semantics and Psychophysical discrimination organization under conditions. task outcomes. thresholds. Behavioral Distribution of declared Internal Controlled comparison over actions/outcomes. interpretation population/context. and unmeasured behavior. Interactional Available Surface form and Bisimulation-like comparison operation-transition-observation internal plus human-use tests. structure. implementation. ---------------------------------------------------------------------------------------------------- Known counterexamples show non-entailment among types. Algebraically equivalent equations can produce different solution strategies. Informationally equivalent graphs and tables can differ in comparison accuracy. Semantically equivalent programs can differ in time, energy, numerical stability, or security side channels. Equal task completion can conceal different understanding, error recovery, and transfer. Behavioral equivalence under one context can disappear after learning or under time pressure. # 7. Invariance Under Projection An unrestricted claim that meaning remains invariant under representation change is too strong. \'Same target\' does not guarantee same content, because a projection may alter categorization, precision, presupposition, indexical frame, or available interpretation. A coherent invariance claim must specify at least six items: the target description; the content or property family asserted invariant; the mapping between forms; the interpretation rules; the admissible contexts and observers; and the metric or tolerance. Let T be a declared target domain, R1 and R2 representation domains, p1:T→R1 and p2:T→R2 projection functions, and J1 and J2 interpretation functions into a comparison domain K. Content invariance for property family Q holds when J1(p1(t)) and J2(p2(t)) agree on Q for all t within the declared domain and tolerance. This is not circular if Q and the interpretation functions are independently specified. It becomes circular when equivalence is defined merely as \'preserving the same meaning\' and meaning is inferred only from judged equivalence. Target invariance, content invariance, meaning invariance, behavioral invariance, task-outcome invariance, and interpretation invariance are independent claims. A target can remain fixed while interpretations vary. Content can be logically invariant while behavior changes. Task outcomes can remain equal while strategies and understanding differ. Interpretation can converge while feasible actions differ. The evidence therefore supports the phrase \'scoped semantic invariance,\' not semantic invariance simpliciter. Formalization is possible where target semantics and correspondence rules are explicit. Empirical testing is required where interpretation depends on human observers, learned conventions, modality, or context. # 8. Epistemic Access and Opportunity Representations actively organize epistemic access. They determine which distinctions are visible without transformation, which comparisons are local, what must be remembered, what can be searched, what errors become salient, and which inferences are executable through perceptual or computational operations. External representations can convert internal computation into perceptual recognition, but they can also conceal provenance or encourage invalid inferences. Opportunity should not be introduced as a replacement for affordance, choice set, action space, or information access. Existing concepts cover much of the terrain. Ecological affordances concern action possibilities relative to organism-environment systems. Decision theory and reinforcement learning formalize available actions and policies. Control theory formalizes reachable states and controllability. HCI distinguishes actual, perceived, and signaled actions. Visualization and external cognition analyze operations and inferential access. A cross-disciplinary analysis nevertheless requires three distinct sets: feasible actions F, signaled or directly discoverable actions S, and believed actions B for an observer in context. Representational change may leave F fixed while changing S and B; it may also change F when the representation is an operative view that permits or blocks transformations. \'Opportunity profile\' is retained only as a descriptive tuple ⟨F,S,B,inferential operations,error-recovery operations,coordination operations⟩, not as a new ontological entity. Representation does not cause behavior directly. A defensible causal model includes representation, observer capabilities and prior knowledge, task, incentives, environment, available operations, and temporal history. Experimental attribution requires manipulation of representation while controlling or measuring these mediators and moderators. # 9. Comparative Cases ## 9.1 One semantic structure as table, graph, map, and narrative Target: a directed network of public-health facilities, referral relations, service capacities, locations, and temporal disruptions. A table preserves attribute values and supports sorting, filtering, and exact lookup; it suppresses path structure unless computed. A node-link graph exposes connectivity and centrality but can obscure exact quantities and geographic distance. A map preserves selected spatial relations and supports regional comparison while distorting geometry according to projection and potentially hiding non-spatial dependencies. A narrative preserves causal or temporal interpretation and supports explanation but linearizes concurrency and makes exhaustive comparison difficult. The target need not change, but no pair is globally equivalent. They may be informationally equivalent if each can be reconstructed from the same dataset, structurally equivalent for selected relations, or task-equivalent for a specific query. Behavioral predictions include faster exact lookup in tables, faster path recognition in graphs, faster spatial clustering judgments in maps, and better causal recall from narrative; these remain empirical hypotheses conditioned on scale, literacy, and task. ## 9.2 One scientific target through equations, diagrams, simulation, and prose Target: a susceptible-infectious-recovered epidemic model with specified parameters and assumptions. Differential equations preserve formal dependencies and permit analytic reasoning. A compartment diagram exposes flows and conservation structure. Simulation exposes trajectories, stochastic variation, and sensitivity under parameter settings. Prose states assumptions, interpretations, and limitations not contained in the equations. The forms are complementary rather than substitutable. Equation and code may disagree through discretization or implementation error; a diagram may omit nonlinear terms; prose may introduce ambiguity. Scientific adequacy requires cross-representation consistency tests. ## 9.3 One computational system through GUI, CLI, API, and conversation Target: a version-control system\'s repository states and operations. A GUI externalizes status and constrains commands, supporting recognition and discoverability. A command line provides compositional, scriptable operations and exact textual traces but requires recall. An API exposes machine-addressable operations, schemas, and errors while omitting interactive guidance. A conversational interface maps natural-language requests to operations, lowering formulation cost but adding interpretive uncertainty and a need for confirmation and provenance. Core repository transitions may be computationally equivalent when each invokes the same validated operations. They are not interactionally equivalent: available compositions, visibility of consequences, error prevention, and auditability differ. Equal task completion does not establish equal understanding or safety. ## 9.4 Accessibility across visual, auditory, and tactile forms Target: a transit network with stations, lines, transfer points, service alerts, and route options. A visual map offers parallel spatial overview. Auditory presentation serializes access and increases memory and navigation costs unless structured for query. A tactile map preserves selected topology and spatial layout but has resolution and labeling constraints. Multimodal forms can preserve route semantics while differing in perceptual access, privacy, scanning time, and error recovery. Accessibility requires content and relations to be programmatically determinable or available in alternative forms, but equivalent access is a performance and usability claim, not a consequence of nominal content duplication. ## 9.5 Informational equivalence with different reasoning The classic isomorphic arithmetic-task results analyzed by Zhang and Norman show that representations distributing information externally can change problem difficulty despite equivalent abstract structure. Visualization research similarly shows that equal numerical data encoded by position, length, angle, area, or color are decoded with different accuracy. These cases falsify the inference from informational equivalence to cognitive or behavioral equivalence. # 10. Candidate Formal Model Projection is defined here as an analytical role: a declared transformation that produces a representation of a target for specified observers and uses. It does not replace \'representation,\' \'encoding,\' \'view,\' \'abstraction,\' \'model,\' or \'simulation\' inside disciplines where those terms are sufficient. It supplies a common comparison schema across them. A projection contract is the tuple Π = ⟨T,R,p,I,P,X,O,A,U,C,E⟩, where T is the source or target domain; R is the representation domain; p is the transformation or construction rule; I is the interpretation rule or practice; P is the preservation profile; X is the transformation, omission, and introduction profile; O is the observer model; A is the available operation set; U is intended use; C is context and scope; and E is error, uncertainty, tolerance, and failure conditions. For a target state t, the representation r=p(t) is scientifically analyzable when the contract permits independent investigators to determine what claims are licensed, which distinctions are unavailable, how operations correspond to target transitions, and under what conditions conclusions fail. The model is deliberately weaker than a universal semantics. It allows formal mappings, physical instruments, public symbols, and learned representational practices. A comparison between projections Π1 and Π2 is made over a declared property family Q and observer-task distribution D. Formal preservation is tested by commuting diagrams, reconstruction, logical consequence, or behavioral refinement where applicable. Empirical access is tested through accuracy, latency, search paths, confidence, error types, learning, transfer, and recovery. Causal claims require randomized or otherwise identified manipulation and mediation analysis where feasible. # 11. Falsification Tests ----------------------------------------------------------------------- **Claim** **Evidence against** **Consequence** ----------------------- ----------------------- ----------------------- Representation requires Stable predictive Revise relational a target and representation relation definition. interpretive rule. definable solely by intrinsic vehicle properties. Equivalence must be One equivalence Collapse taxonomy. typed. relation proven to preserve all scientifically relevant properties across domains. Informational Controlled studies Remove behavioral equivalence does not consistently show separation. imply behavioral identical action equivalence. distributions across informationally equivalent forms and populations. Scoped semantic No non-circular Reject invariance is coherent. independent semantic-invariance specification of language. content and interpretation can be constructed even in formal cases. Projection adds Existing single Use that framework; cross-disciplinary framework already discard projection value. covers formal contract. preservation, human epistemic access, operations, uncertainty, and failure without translation loss. Representations After controlling task, Restrict claim to organize epistemic observer, operations, formal access only. access. and context, representational manipulation produces no reliable differences in access measures. Opportunity profile is Affordance, Adopt established not reducible to one action-space, or view construct exclusively. existing construct. theory fully captures feasible, signaled, believed, inferential, recovery, and coordination operations. Representation and Preservation and Treat separation as implementation can operation claims cannot domain-limited. often be separated. be stated independently of device, rendering, data structure, or execution substrate in target cases. ----------------------------------------------------------------------- The most damaging result would be demonstration that the projection contract merely restates an existing general theory with no added comparative predictions or measurement discipline. The framework therefore earns retention only if it improves cross-form specification, reveals hidden non-equivalences, or supports reproducible comparative experiments. # 12. Threats to Validity Construct validity is threatened by polysemy. \'Representation,\' \'model,\' \'meaning,\' \'information,\' and \'equivalence\' change across traditions. The paper mitigates this by defining roles and typed relations rather than asserting lexical identity. External validity is threatened by moving from formal domains with stipulated semantics to human contexts with negotiated interpretation. Formal claims are therefore not generalized without observer and context variables. Selection bias remains because the literature is too large for exhaustive review. The synthesis favors foundational accounts and explicit formalizations, potentially underrepresenting practice-based, non-Western, phenomenological, and artistic theories. Empirical claims in visualization and cognition often use restricted tasks and participant populations. Accessibility equivalence is especially sensitive to heterogeneous capabilities and technologies. Causal validity is limited. Observed differences between representations may arise from familiarity, training, ordering, modality, incentives, or implementation quality. Studies must control content and available operations while avoiding the false assumption that surface matching controls interpretation. Finally, the proposed contract may be too general to generate novel predictions; its value should be judged by comparative use, not conceptual elegance. # 13. Implications for Interaction Research Interaction research should not posit an observer-independent semantic state merely because multiple interfaces address a common backend object. It should declare the target description and authority that stabilizes it. Representation, opportunity, interpretation, action, and outcome should remain separate variables. Feasible actions may be invariant while signaled and believed actions vary; identical actions may be interpreted differently; equal outcomes may arise through different strategies. Representation similarity should be typed. A GUI and API may be computationally equivalent but perceptually and interactionally dissimilar. Behavioral equivalence requires a population, context, task distribution, metrics, and tolerance. Transfer between representations should be analyzed through preserved conceptual relations, learned operations, and changed cues rather than through visual resemblance alone. The projection contract can support experiments by making manipulation explicit. Researchers can hold target and task constant, vary one projection property, measure epistemic access and opportunity profiles, and test mediators such as salience, memory load, inferred action set, or confidence. This creates falsifiable work without presuming a new discipline or ontology. # 14. Conclusion Cross-disciplinary evidence rejects a unitary theory in which representation is resemblance, encoding, formal mapping, mental state, or public artifact alone. It also rejects absolute equivalence and unrestricted semantic invariance. Representations are selective, rule-governed means of access to declared targets within interpretive practices. They preserve some distinctions, transform or omit others, and introduce operations and organizational effects. Existing theories are powerful but fragmented by domain. Model theory, morphisms, information theory, abstract interpretation, observational equivalence, database views, lenses, cartographic projection, semiotics, scientific modeling, and external cognition already explain major components. No evidence supports replacing them with a wholly new representation theory. A general theory of projection is justified only as a shared analytical contract that coordinates those established mechanisms and requires explicit scope conditions. Final determination: 3. A general theory of projection is justified, but semantic invariance requires strict scope conditions. # 15. Reusable Representation-Analysis Framework ## A. Representation Taxonomy ----------------------------------------------------------------------------------------- **Type** **Defining **Primary preservation concern** **Typical risk** relation** ----------------- ----------------- ---------------------------------- ------------------ Indexical / Causal or Traceability, quantity, Instrument bias or measurement calibrated uncertainty. invalid relation to calibration. target. Symbolic / Conventional sign Reference and inferential role. Ambiguity and linguistic system and context shift. interpretation. Structural / Mapping between Selected relations and operations. Mistaking partial mathematical relational for total structures. isomorphism. Model / Purposeful Empirical and explanatory Idealization scientific surrogate used relevance. outside scope. for inference. Diagrammatic / Spatial encoding Topology, order, magnitude, Perceptual visual of relations or grouping. distortion or quantities. salience bias. Narrative Temporally and Sequence, agency, explanation. Linearization and causally selective framing. organized discourse. Encoding / code Rule-based Decodability and error bounds. Semantic transformation of indeterminacy. symbols or signals. Abstraction Sound Specified properties or judgments. False approximation of completeness. a richer domain. View / projection Derived exposure Query answers and update Hidden source of source correspondence. distinctions. structure. Simulation Executable model Dynamic behavior under Implementation and producing assumptions. parameter trajectories. artifacts. Interface / Observable and Operation-transition-observation Confusing operative manipulable relation. discoverability representation access surface. with feasibility. Internal State posited to Explanatory role in cognition. Unobservable or cognitive carry content and theory-dependent guide processing. content. ----------------------------------------------------------------------------------------- ## B. Equivalence Matrix Use the typed equivalence table in Section 6. Every equivalence claim must complete: type; invariant; admissible difference; observer; task; context; metric; tolerance; and test. Multiple types may be asserted, but none may be inferred from another without evidence. ## C. Projection Contract ----------------------------------------------------------------------- **Field** **Required declaration** ----------------------------------- ----------------------------------- Target domain What is represented; authority and version; boundaries and granularity. Representation domain Vehicle/form and admissible instances. Mapping Construction, encoding, measurement, query, or transformation rule. Interpretation Semantics, conventions, training, and decoding assumptions. Preserved properties Relations, quantities, behaviors, consequences, or operations retained. Transformed properties Changes of coordinate, scale, order, granularity, modality, or dynamics. Omitted properties Distinctions unavailable or unrecoverable. Introduced properties Categories, saliences, defaults, ambiguity, artifacts, or noise. Available operations Read, query, compare, manipulate, update, undo, coordinate, export. Observer assumptions Capabilities, knowledge, language, access needs, and role. Intended use Questions, decisions, tasks, and prohibited uses. Uncertainty and error Provenance, confidence, distortion, latency, and tolerance. Failure conditions Known counterexamples, out-of-scope states, and invalid inferences. ----------------------------------------------------------------------- ## D. Representation Comparison Protocol 1. Declare one target and its authoritative boundaries without assuming observer-independent meaning. 2. Inventory each representation vehicle, mapping, interpretation rule, and available operation. 3. Specify candidate invariants and the equivalence type for each; reject untyped equivalence claims. 4. Construct preservation, transformation, omission, and introduction profiles. 5. Hold target content and task constant where possible; record unavoidable implementation differences. 6. Declare observer population, prior knowledge, modality, context, and accessibility conditions. 7. Measure formal correctness separately from epistemic access, task performance, behavior, learning, and transfer. 8. Test operation correspondence, error recovery, uncertainty communication, and update semantics. 9. Analyze mediation and moderation rather than attributing behavior directly to representation. 10. Report scope, tolerances, contradictory results, and conditions under which equivalence fails. ## E. Falsification Matrix Use the matrix in Section 11 as the minimum test set. Any application should add domain-specific failure conditions and identify which result would require abandoning, narrowing, or replacing the projection analysis. # 16. References Blackwell, A. F., Britton, C., Cox, A., Green, T. R. G., Gurr, C., Kadoda, G., Kutar, M., Loomes, M., Nehaniv, C., Petre, M., Roast, C., Roes, C., Wong, A., & Young, R. M. (2001). Cognitive dimensions of notations: Design tools for cognitive technology. In Cognitive Technology. Bohannon, A., Pierce, B. C., & Vaughan, J. A. (2006). Relational lenses: A language for updatable views. PODS. Card, S. K., Mackinlay, J. D., & Shneiderman, B. (Eds.). (1999). Readings in information visualization. Morgan Kaufmann. Cleveland, W. S., & McGill, R. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79, 531-554. Codd, E. F. (1970). A relational model of data for large shared data banks. 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Usability analysis of visual programming environments: A cognitive dimensions framework. Journal of Visual Languages & Computing, 7, 131-174. Hutchins, E. (1995). Cognition in the wild. MIT Press. Johnson-Laird, P. N. (1983). Mental models. Harvard University Press. Kosslyn, S. M. (1994). Image and brain. MIT Press. Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-100. Marr, D. (1982). Vision. W. H. Freeman. Milner, R. (1989). Communication and concurrency. Prentice Hall. Norman, D. A. (1988). The psychology of everyday things. Basic Books. Palmer, S. E. (1978). Fundamental aspects of cognitive representation. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization. Erlbaum. Peirce, C. S. (1931-1958). Collected papers of Charles Sanders Peirce. Harvard University Press. Rothenberg, J. (1989). The nature of modeling. In L. E. Widman, K. A. Loparo, & N. R. Nielsen (Eds.), Artificial intelligence, simulation, and modeling. Wiley. Saussure, F. de. (1983). Course in general linguistics. Duckworth. (Original work published 1916). Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379-423, 623-656. Shimojima, A. (2015). Semantic properties of diagrams and their cognitive potentials. CSLI Publications. Spence, R. (2007). Information visualization: Design for interaction (2nd ed.). Pearson. Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103, 677-680. Suchman, L. A. (1987). Plans and situated actions. Cambridge University Press. Tarski, A. (1944). The semantic conception of truth and the foundations of semantics. Philosophy and Phenomenological Research, 4, 341-376. Tufte, E. R. (1983). The visual display of quantitative information. Graphics Press. Ware, C. (2012). Information visualization: Perception for design (3rd ed.). Morgan Kaufmann. W3C. (2023). Web Content Accessibility Guidelines (WCAG) 2.2. World Wide Web Consortium. Woodward, J. (2003). Making things happen: A theory of causal explanation. Oxford University Press. Zhang, J., & Norman, D. A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18, 87-122. ======================================================================== ## FILE: docs/02_Research_Papers/04_Representation_and_Projection/Scoped_Invariance_Under_Projection_v0.4.md (291 lines, 9.9 KiB) ======================================================================== # Scoped Invariance Under Projection ## Typed Preservation Across Computational Representations **Version:** Draft 0.4 **Status:** Proposed Theory ## Abstract Unqualified semantic invariance under projection is too strong. Representations are selective and constructive. They may preserve identities, relations, denotations, transitions, or task-relevant distinctions while changing salience, grouping, access paths, available operations, interpretation, effort, and behavior. The defensible principle is scoped and typed: > A projection may preserve declared ontological, semantic, informational, structural, computational, inferential, task, behavioral, opportunity, or interactional properties only under specified target, mapping, interpretation, observer, context, metric, and tolerance conditions. This paper states the current theory and incorporates the later findings on relational meaning, typed opportunity, strict interaction episodes, measurement, similarity, and strategy. ## 1. Target and representation A representation is not identical with its target. A representation relation minimally involves: - a target or source domain; - a realized vehicle; - a mapping or construction rule; - an interpretation rule or practice; - an observer or use context. A projection is the declared transformation that produces the accessible representation. ## 2. Relational meaning The source model is not a single observer-independent semantic layer. Relevant roles include: - domain commitments; - system state; - semantic assignment; - projection; - representation; - interpretation; - opportunity; - behavior. They are distinguishable but recursively related. Representation and interpretation may revise later semantics or ontology. Behavior changes state and future opportunity. ## 3. Representation is constructive A projection may introduce properties absent from the source description: - coordinate systems; - ordering; - grouping; - hierarchy; - proximity; - salience; - defaults; - notation; - modality; - interaction operations; - latency; - ambiguity; - perceptual cost; - recovery paths. A dependency graph rendered as a table and as a spatial network can preserve declared edges while creating different comparison and action structures. ## 4. Typed invariance An invariance claim must declare what remains stable. ### Ontological invariance Declared entities, identity conditions, categories, or relations remain stable. ### Semantic invariance Denotation, truth conditions, operational behavior, or inferential consequences remain stable under a specified semantics. ### Informational invariance Declared distinctions remain recoverable under a specified source, code, model, relevance relation, or distortion measure. ### Structural invariance Selected relations and operations are preserved. ### Topological invariance Continuity, adjacency, or neighborhood relations are preserved. ### Computational invariance Declared observable execution behavior is equivalent. ### Inferential invariance Answers or consequences for a specified query or logic class are preserved. ### Task invariance Outcome distributions remain within tolerance for a specified task and population. ### Behavioral invariance Declared action or outcome distributions remain within tolerance for a specified population and context. ### Opportunity invariance The relevant feasible, permitted, enabled, reachable, exposed, signaled, believed, and recoverable action relations remain equivalent for a declared agent class and task. ### Interactional invariance The participant-coupling-transition-recurrence structure remains equivalent under specified boundaries, timescales, authority, task, context, observables, and tolerance conditions. ### Measurement invariance The relation between observations and measured variables remains sufficiently stable across groups, modalities, instruments, or contexts to support the intended comparison. ### Strategy invariance A declared higher-order organization of criteria, state abstraction, information policy, conditional selection, commitment, recovery, and switching remains equivalent across contexts, even when surface actions or traces differ. No type entails another without evidence. ## 5. Formal condition Let: - `T` be the declared target domain; - `R₁` and `R₂` be representation domains; - `p₁: T → R₁` and `p₂: T → R₂` be projection functions; - `J₁` and `J₂` be independently specified comparison or interpretation functions; - `Q` be the property family claimed invariant; - `D` be the observer-task-context distribution; - `ε` be the tolerance. Scoped invariance holds when `J₁(p₁(t))` and `J₂(p₂(t))` agree on `Q` within `ε` for all relevant `t` and conditions in `D`. The claim is circular when `Q` is defined only as “the meaning judged to be the same.” ## 6. Opportunity under projection Projection affects more than visibility. For an action, distinguish: - domain validity; - capability; - permission; - current enablement; - reachable outcomes; - exposure; - signaling; - believed availability; - expected consequence; - reversibility; - selection; - execution; - success. A projection may preserve transition semantics while changing exposure, signaling, belief, path length, feedback, recovery visibility, or auditability. It may also change actual feasibility by gating operations. Therefore: > Semantic equivalence does not imply opportunity equivalence. And: > Opportunity equivalence does not imply behavioral or interpretive equivalence. ## 7. Comparison protocol A valid comparison should: 1. declare the target, ontology or domain commitments, action vocabulary, and authority; 2. declare each projection contract; 3. verify transition-level and semantic equivalence independently; 4. specify the candidate invariance type; 5. inventory preservation, transformation, omission, and introduction; 6. inventory feasible, permitted, enabled, reachable, exposed, signaled, and recoverable actions; 7. declare observer population, language, training, modality, accessibility, task, and context; 8. measure believed actions and expected consequences separately from behavior; 9. distinguish direct observations, derived features, and latent inference; 10. control latency, reliability, familiarity, motor cost, implementation quality, and order; 11. state metrics, uncertainty, tolerances, and failure conditions. ## 8. Evidence requirements Formal preservation and empirical equivalence require different evidence. Formal evidence may include: - stable identifiers; - commuting diagrams; - logical consequence; - query equivalence; - refinement; - bisimulation; - reconstruction; - constraint satisfaction; - verified transition correspondence. Empirical evidence may include: - discovery rates; - latency; - belief calibration; - action sequences; - error types; - recovery; - learning; - transfer; - confidence; - strategy diversity; - accessibility and effort. Equal task completion alone is insufficient. ## 9. Typed comparison and incomparability Scoped invariance is one part of the broader Interaction Similarity framework. A comparison must distinguish token identity, type identity, exact equivalence, approximate equivalence, graded similarity, unknown status, and incomparability. A comparison specification should declare: ```text K = ``` A projection pair may be semantically equivalent but opportunity-different, trace-similar but causally different, or outcome-equivalent but strategy-different. When boundaries, correspondence mappings, scales, observation models, or validity domains cannot be aligned without unsupported assumptions, the correct result is incomparable rather than a forced low score. Scalar aggregation is optional and requires a defensible measurement model. It must not allow a critical failure in permission, accessibility, safety, or recovery to be numerically hidden by superficial similarity elsewhere. ## 10. Implications for Fundamental Fundamental should support scoped invariance by making the following explicit: - domain and state authority; - identities and relation semantics; - transition rules; - projection contracts; - exposed operations; - omitted and introduced properties; - snapshots, diffs, and replay; - numeric and temporal tolerances; - host-specific limitations. Fundamental can verify many formal invariants. Behavioral, interpretive, and opportunity claims require external empirical studies. ## 11. Falsification The theory should be narrowed or rejected if: - candidate invariants cannot be specified independently; - projection contracts reveal no useful non-equivalence; - one established framework provides the same comparative discipline with fewer assumptions; - representation and implementation cannot be separated in the target domain; - typed opportunity variables cannot be measured reliably; - controlled projection changes produce no access, opportunity, behavior, learning, or transfer differences; - scoped invariance adds no explanatory, predictive, or intervention gain. ## 12. Limits Scoped invariance does not imply: - complete preservation; - observer-independent meaning; - identical interpretation; - equal understanding; - equal accessibility; - equal cognitive effort; - equal behavior; - equal recovery; - cultural neutrality; - implementation independence in every domain. ## Conclusion The scientifically defensible principle is not that reality or meaning remains unchanged whenever a projection changes. It is: > **Declared properties may remain invariant across projections only within explicit scope, interpretation rules, observer conditions, equivalence type, measurement procedure, and tolerance.** The strength of the principle comes from what it forces researchers and system builders to declare. Projection becomes scientifically useful when preservation and difference are inspectable rather than assumed. ======================================================================== ## FILE: docs/02_Research_Papers/05_Ontology_Semantics_Interpretation/Ontology_Semantics_Representation_and_Interpretation.md (919 lines, 52.1 KiB) ======================================================================== **Ontology, Semantics, Representation, and Interpretation** *Toward a Layered Theory of Computational Meaning* Formal research paper \| July 2026 **Final determination** **Yes. The concepts can be organized into a coherent computational theory, provided the theory is relational rather than a fixed linear pipeline and distinguishes formal semantics from observer interpretation.** # Abstract Ontology, semantics, representation, information, interpretation, and behavior are often arranged as if they formed a simple stack. Cross-disciplinary analysis shows that the distinctions are real, but the stack is too strong. Philosophical ontology studies what exists and how categories of being are related; computational ontologies specify a vocabulary and constraints for a domain. Formal semantics assigns denotations, truth conditions, transitions, or observable behavior to well-formed expressions. Information measures or characterizes distinctions, correlations, descriptions, or truth-bearing content under different theories. Representation is a vehicle-target relation that selectively preserves and exposes structure. Interpretation is the situated application of rules, conventions, prior knowledge, and goals by a system or community. Behavior is a causal outcome produced by an agent-system-environment process and is not entailed by representation or interpretation alone. The evidence supports a coherent computational theory, but not the proposed one-way sequence Ontology -\> Semantic State -\> Representation -\> Interpretation -\> Behavior. Ontology and semantics are mutually constraining specifications; representations may encode syntactic structures, semantic structures, or both; interpretation can establish, recover, revise, or reject semantic assignments; information is typed and may exist without meaning in Shannon\'s sense; and behavior feeds back into interpretation and model revision. The minimal architecture therefore consists of six roles linked by typed relations: domain commitments, system state, semantic assignment, representational realization, interpretive process, and situated action, with information defined relative to a chosen theory and projection defined as a declared transformation between target and accessible vehicle. The distinctions are largely established separately in philosophy, logic, programming languages, ontology engineering, semiotics, and cognitive science. The warranted contribution is a cross-disciplinary synthesis and diagnostic framework, not a new foundational vocabulary. Primary contribution: computational meaningfulness should be analyzed as a constrained relation among domain commitments, formal or socially stabilized semantic assignments, representational vehicles, interpreters, and action contexts; no single layer possesses meaning in isolation. # 1. Motivation Computational systems manipulate physical states according to engineered rules. Humans and other systems nevertheless treat some of those states as files, instructions, maps, prices, permissions, identities, or claims. The central theoretical problem is not whether bits can be arranged into layers. It is what licenses movement from physical or formal difference to semantic significance, and which distinctions survive changes of notation, modality, implementation, or observer. Conflation creates recurrent errors. A database schema is called an ontology although it may encode only local storage constraints. A symbol is said to contain meaning although its denotation depends on a semantic interpretation. A user interface is described as the semantic layer although it is one representation of system state. Successful behavior is treated as proof of shared understanding although equivalent outcomes may arise from different interpretations, heuristics, or accidents. Conversely, strong anti-representational arguments sometimes deny distinctions that formal computer science demonstrably uses to prove compiler correctness, program equivalence, and knowledge-base entailment. This paper asks one question: Can ontology, semantics, representation, interpretation, and behavior be organized into a coherent computational theory without contradicting existing philosophy and computer science? The test is conservative. A distinction is retained only when established theories assign it a separable explanatory role or when its removal produces a demonstrable loss of explanatory power. # 2. Literature Review ## 2.1 Method The review is a structured conceptual synthesis of foundational and primary sources from analytic philosophy, formal ontology, knowledge representation, model theory, programming-language semantics, information theory, semiotics, cognitive science, linguistics, distributed cognition, cybernetics, information science, and HCI. Sources were selected when they define one of the focal concepts, specify a formal relation among them, or provide a counterargument to their separation. Each source was coded for: the relata it presupposes; whether meaning is intrinsic, assigned, causal, inferential, or use-dependent; whether an interpreter is explicit; whether the account is formal or empirical; and what would count as identity or change. Prior project papers were used only as background and consistency constraints, not as evidence for the layered model. ## 2.2 Foundational tensions - Realism versus conceptualism: ontology may concern reality itself or an explicit conceptualization used by a community. - Truth-conditional versus use-based semantics: meaning may be modeled by denotation and truth conditions, inferential role, convention, intention, or practical use. - Intrinsic versus derived intentionality: computational states may possess only observer-relative meaning, or may acquire content through causal, functional, biological, or social relations. - Syntactic versus semantic information: Shannon information excludes meaning, while semantic theories add truth, reference, relevance, or viability conditions. - Internal versus distributed interpretation: interpretation may be assigned to an individual mind, a formal evaluator, an organization, or a coupled cognitive system. - Linear versus recursive architecture: software diagrams often imply a pipeline, whereas semiotics, learning, and interaction require feedback and revision. # 3. Existing Definitions ## 3.1 Ontology In philosophical usage, ontology concerns what exists and the most general categories and relations of being. It asks what kinds of entities there are, what identity conditions they possess, and how dependence, parthood, persistence, possibility, and modality are structured. This is not a data model and not a vocabulary file. In AI and information systems, an ontology is an explicit specification of a conceptualization, later refined as a formal specification of a shared conceptualization. Gruber\'s account emphasizes representational vocabulary and portability; Guarino distinguishes a conceptualization from the logical theory that approximates its intended models. Computational ontologies commonly contain classes or types, relations, functions or properties, individuals, axioms, constraints, and sometimes processes, temporal relations, or modal commitments. OWL supplies a formal syntax and model-theoretic semantics for such specifications. A domain ontology is reusable commitment about a domain. A conceptual model is usually designed for a particular application. A schema constrains the organization and validity of stored or exchanged data. A taxonomy primarily orders categories, typically through broader-narrower or subtype relations. These artifacts may overlap, but none is interchangeable with philosophical ontology. ----------------------------------------------------------------------------------- **Term** **Primary role** **Typical **What it does not contents** by itself establish** ---------------------- ---------------------- ------------------ ------------------ Philosophical ontology Account of being and Entities, A machine-readable categories identity, vocabulary dependence, modality, relations Formal ontology Domain-independent Parthood, A local structural theory dependence, application schema universals, particulars, time Computational/domain Shared explicit domain Classes, That the modeled ontology commitment relations, axioms, categories are constraints, metaphysically instances fundamental Conceptual model Application-oriented Entities, Reusable domain abstraction relationships, consensus processes, rules Schema Data structure and Fields, types, Meaning beyond validity constraints keys, declared or cardinalities external semantics Taxonomy Classification Categories and Rich relational or hierarchy broader/narrower modal theory relations ----------------------------------------------------------------------------------- ## 3.2 Semantics Semantics is not one relation. In formal logic, an interpretation maps nonlogical vocabulary to a domain and assigns truth conditions to sentences. Tarski\'s work sharply separates object language and metalanguage and defines truth for formalized languages relative to an interpretation. Model theory generalizes this relation between formal languages and structures. Programming-language semantics assigns mathematical meaning or execution behavior to programs. Denotational semantics maps expressions to mathematical objects; operational semantics specifies transitions of an abstract machine; axiomatic semantics characterizes programs through assertions and proof rules. These are alternative semantic descriptions of computation, not psychological interpretation by users. Compiler correctness is usually expressed as preservation or refinement between source and target semantics, showing that representation and implementation may change while declared behavior remains equivalent. Linguistics and philosophy of language introduce truth conditions, reference, compositionality, sense, speaker meaning, convention, context, and pragmatic enrichment. Semiotics treats signification as a triadic or systemic relation. Cognitive and embodied approaches add grounding in perception, action, and environment. Consequently, a general definition must avoid identifying semantics solely with human understanding or solely with formal denotation. Canonical definition used here: semantics is a rule-governed assignment of content, denotation, truth conditions, inferential role, or behavior to expressions, states, or signs within a specified system and domain. A semantic state is the currently applicable set of content-bearing assignments and relations under that semantics. It is not assumed to be observer-independent; its status depends on whether the semantic theory is formal, social, biological, or psychological. ## 3.3 Representation Representation is a selective relation among a vehicle, a target, a mapping or correspondence, and an interpretive practice. A representation may be physical or formal; internal or public; symbolic, iconic, indexical, diagrammatic, linguistic, numerical, or executable. It can encode syntax without preserving target meaning, encode a semantic model, or provide an interface through which semantic consequences become inspectable and actionable. Representations do not possess semantics in one uniform sense. In a formal system, a representation has assigned semantics by definition of an interpretation function. In social practice, a sign vehicle carries conventional or use-stabilized meaning. In cognition, content may depend on causal, teleological, functional, inferential, or ecological relations. The vehicle alone is insufficient in every account except a strong intrinsic-content theory, for which computational evidence is weak and philosophical controversy remains substantial. ## 3.4 Interpretation Interpretation has at least three established senses. In logic, an interpretation is a mathematical assignment from vocabulary to a domain. In semiotics and philosophy of language, interpretation is the production or uptake of significance under conventions, context, and inferential practices. In cognition and HCI, interpretation is an empirically realized process by which an agent forms beliefs, expectations, classifications, or action-relevant understandings from available signs. These senses must not be collapsed. A model-theoretic interpretation can be completely specified without a conscious interpreter. A human interpretation can diverge from the intended formal semantics. Multiple human or institutional interpretations may coexist for the same vehicle, and one observer may revise interpretation after action or feedback. Canonical definition used here: interpretation is the application or construction of semantic relations by an interpreting system under a context, competence, history, and purpose. Its result may be a denotation, belief, inference, expectation, classification, or action policy. Interpretation differs from semantics because semantics specifies or stabilizes admissible content relations, whereas interpretation is an event, process, or act that applies, recovers, negotiates, or revises them. ## 3.5 Information Shannon information quantifies uncertainty and coding constraints over possible messages; it explicitly brackets meaning. Algorithmic information measures description length relative to a machine. Semantic information theories add well-formedness, meaningfulness, truth, reference, or causal relevance. Ecological information concerns structured invariants available in organism-environment relations. Pragmatic accounts concern information\'s effect on decision, action, or viability. No unqualified statement such as \'the information remained the same\' is therefore acceptable. The theory, random variables or description language, semantic interpretation, task, observer, and tolerance must be named. A byte-preserving transformation may preserve Shannon information while changing meaning through a different codebook; a lossy representation may reduce recoverable data yet preserve all information relevant to a task. Canonical definition used here: information is a typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, or use. Information is not treated as a synonym for data, meaning, or interpretation. ## 3.6 Projection Projection is retained as an analytical role rather than a new substance. It is a declared transformation from a target description or state into an accessible representational form under a contract that identifies preserved, transformed, omitted, and introduced properties, available operations, observer assumptions, intended uses, and failure conditions. The term coordinates existing notions such as abstraction functions, views, encodings, lenses, simulations, and model morphisms. It adds value only when this declaration is explicit. # 4. Comparative Analysis --------------------------------------------------------------------------------------- **Concept** **Question **Primary **Identity **Characteristic answered** relata** criterion** failure** ---------------- -------------- --------------- ----------------- --------------------- Ontology What entities Domain, Same commitments Category error or and relations categories, or intended incompatible are admitted? identity and models under commitment constraints declared scope Semantics What do Syntax/state, Same denotation, Undefined, ambiguous, expressions or domain/model, truth conditions, inconsistent, or states denote, assignment transition non-compositional imply, or do? rules behavior, or assignment consequences Information What Source, Same measure, Loss, noise, distinctions alternatives, recoverability, falsehood, or content are code or truth-bearing irrelevance, or available semantic content, or theory mismatch under a relation relevance theory? Representation What vehicle Vehicle, Typed Omission, distortion, gives target, preservation opacity, or selective mapping, under a declared unsupported inference access to what practice equivalence target? Interpretation How is Interpreter, Convergent Misinterpretation, significance vehicle, denotation, underdetermination, applied or context, belief, or disagreement constructed? conventions, inference, or goals policy under scope Behavior What does the Agent/system, Equivalent Performance situated environment, observable action divergence, system do? state, action, traces or adaptation, or feedback outcomes under confounding conditions --------------------------------------------------------------------------------------- ## 4.1 What is separable? Ontology and semantics are distinguishable but interdependent. An ontology supplies or constrains the kinds of entities over which a semantics ranges; a semantics makes the ontology\'s expressions truth-evaluable or inferentially usable. Ontology without semantics may be an uninterpreted signature or informal categorization. Semantics without ontological commitment is impossible in a broad Quinean sense because variables and denotations range over something, but it need not commit to a rich domain ontology. Semantics and representation are distinguishable because multiple syntactic or material vehicles can receive the same semantic assignment, and one vehicle can receive different assignments under different interpretations. Formal semantics relies on representations to state expressions, models, and rules, but does not identify those tokens with their denotations. Semantics and interpretation partially overlap in ordinary language but separate in formal and empirical analysis. Formal semantics can be stipulated independently of any person\'s success in interpreting it. Human interpretation can be studied as a process that approximates, contests, or ignores intended semantics. Behavior is downstream only in a weak causal sense. Semantic and representational structures constrain possible behavior, but action also depends on goals, memory, competence, attention, incentives, embodiment, environmental state, and stochasticity. Behavior supplies evidence about interpretation but never uniquely identifies it without additional assumptions. # 5. Candidate Layered Model ## 5.1 Rejection of the simple chain The candidate chain Ontology -\> Semantic State -\> Representation -\> Interpretation -\> Behavior is rejected as a universal architecture for four reasons. First, ontologies are themselves representations with semantics. Second, representations can precede or induce semantic stabilization rather than merely render a prior semantic state. Third, interpretation may modify the effective ontology and semantic state. Fourth, behavior feeds back through observation, learning, and institutional revision. ## 5.2 Minimal relational architecture The minimum supported architecture contains six roles and seven typed relations. Roles are not implementation layers; one artifact may realize several roles, and one role may be distributed across artifacts and agents. -------------------------------------------------------------------------- **Role** **Formal symbol** **Definition** ----------------------- ----------------------- -------------------------- Domain commitments O Admissible entity, relation, identity, modality, and constraint commitments for the inquiry or system. System state X Physical, computational, social, or modeled condition at a time. Semantic assignment S Rule-governed assignment of denotation, content, truth conditions, inferential consequences, or transition behavior. Representational R Vehicle or structure realization providing selective access to a target under a mapping. Interpretive process I Contextual application, recovery, negotiation, or revision of semantic relations by a system or practice. Situated behavior B Observable action or state transition produced in an agent-system-environment context. -------------------------------------------------------------------------- Core relations: - Commitment: O constrains the admissible domains and identity conditions of S. - Realization: a projection P maps selected aspects of X or S into R under an explicit preservation contract. - Interpretation: I applies an interpretation function or learned practice to R in context C, yielding an interpreted state J. - Affordance and policy mediation: J, goals G, capabilities K, and environment E jointly constrain an action policy pi. - Behavior: B is sampled or produced from pi under current conditions; it is not a direct function of R alone. - Evidence: observations of B and X update beliefs about I, S, or O but underdetermine them without intervention or auxiliary assumptions. - Feedback: interpretation and behavior may revise O, S, P, conventions, and future state. A compact expression is: **R = P(X, S \| O, Cₚ); J = I(R \| C, H, K); B \~ π(J, G, E, K); observations update {O, S, P, I, π}** This formalization is intentionally schematic. It blocks three invalid inferences: same representation implies same interpretation; same information implies same semantics; and same behavior implies same understanding. # 6. Cross-Disciplinary Synthesis ------------------------------------------------------------------------------------------------------------------------------------------------------------- **Discipline** **Ontology-equivalent** **Semantics-equivalent** **Representation-equivalent** **Interpretation-equivalent** **Behavior/evidence** ---------------- ------------------------- -------------------------- ------------------------------- ------------------------------- ----------------------- Analytic Ontological commitments; Reference, truth Signs, sentences, models Speaker/hearer uptake; Judgments, assertions, philosophy categories conditions, sense, use interpretive charity inferential practice Formal Domain and signature Satisfaction and Formulas, structures, proofs Mathematical assignment, not Entailment and proof logic/model interpretation functions psychological uptake consequences theory Programming Types, values, stores, Denotational, operational, Source, AST, IR, bytecode Evaluator/compiler and Execution traces, languages events axiomatic semantics programmer understanding outputs, safety properties AI/knowledge Domain ontology and Model-theoretic or Knowledge base, graph, Reasoner or agent use; human Entailments, decisions, representation predicates procedural meaning embeddings reading plans Information Entities, concepts, Aboutness, indexing Metadata, records, Indexer and seeker Retrieval, selection, science document kinds meaning, relevance classifications interpretation use Linguistics Discourse entities and Lexical, compositional, Utterances, syntax, gesture Pragmatic enrichment and Responses, inferences, event structures dynamic semantics discourse update coordination Cognitive World and task models Mental content, Internal/external structures Perceptual and cognitive Choice, recall, science inferential or functional construction learning, action role HCI Task and system entities Intended system and domain Interface states and User sense-making and system Interaction traces and meaning interaction forms inference outcomes ------------------------------------------------------------------------------------------------------------------------------------------------------------- # 7. What Actually Changes? ---------------------------------------------------------------------------------------------------------------------------------------- **Transformation** **Ontology** **Semantics** **Information** **Representation** **Interpretation** **Behavior** -------------------- ---------------- ---------------------- ----------------- -------------------- -------------------- --------------- Notation change Usually Invariant only under May preserve Changes May change effort or May change invariant if semantics-preserving formal content; error speed/error symbols are translation description despite systematically length changes semantic renamed equivalence Visualization change Usually Declared relations may Recoverability Changes Inference and Comparison, invariant be preserved and salience can substantially attention may change search, and selectively change error behavior often change Natural-language Target Translation may Semantic and Changes Culture and Coordination change commitments may preserve propositions pragmatic content competence alter and decision remain; lexical imperfectly may shift uptake behavior may categories may change not align Modality change Can remain Can remain invariant Channel capacity Changes Perceptual Latency, invariant under scoped content and processing differs workload, mapping recoverability access, and differ error differ Interaction System domain Operation denotations Available state Interactive Action expectations Feasible and technique change may remain may remain evidence can representation change selected action differ changes sequences change Rendering technology Normally Normally invariant if Signal properties Material realization May change under Can change change invariant rendering is faithful may change changes perceptual through constraints latency, fidelity, or accessibility Implementation Can remain Behavioral semantics Internal Internal Human interpretation Observable change invariant must be proved descriptions and representations may be unaffected behavior preserved, not assumed traces change change invariant only under specified equivalence ---------------------------------------------------------------------------------------------------------------------------------------- # 8. Comparative Case Studies ## 8.1 Mathematical theorem Target: a theorem and its proof-theoretic or model-theoretic consequences. Ontology: mathematical objects, relations, and proof objects admitted by the foundational system. Semantic structure: satisfaction, entailment, and validity. Representations: symbolic notation, geometric diagram, prose proof, and executable proof assistant term. A notation change can preserve formal semantics while changing cognitive accessibility. A diagram may expose invariants and suppress exceptional cases. A proof assistant representation adds machine-checkable dependencies and removes some pragmatic ambiguity. Equivalent theorem statements do not imply equivalent proof understanding. ## 8.2 Transportation network Target: locations, connections, schedules, capacities, and routing constraints. A geographic map preserves spatial geometry; a subway diagram preserves connectivity and ordering while distorting distance; an adjacency matrix preserves edge incidence and supports algebraic operations; a routing graph adds weights and operational constraints. The ontology can remain approximately stable while semantic relations and available information differ by scope. Interpretation depends on the user\'s task: navigation, network planning, accessibility assessment, or capacity optimization. Behavioral route choice can change without any change to the underlying network. ## 8.3 Computational workflow Target: a computation and its permitted state transitions. Source code, abstract syntax tree, bytecode, execution graph, and user interface are not simply visual variants. They expose different entities and operations. A compiler seeks semantic preservation between source and target under a declared observation relation. The AST preserves syntactic composition; bytecode preserves executable behavior but can obscure source abstractions; an execution graph exposes causal or control dependencies; a UI exposes selected domain actions rather than program operations. Human interpretation and behavior vary by representation even where compiler-level observational equivalence holds. # 9. Counterarguments and Falsification ------------------------------------------------------------------------ **Claim under test** **Contrary evidence or **Consequence** argument** ----------------------- ------------------------ ----------------------- Ontology and semantics Every semantics Treat them as are separable quantifies over or distinguishable roles denotes some domain; with mutual intended models partly constraints, not constitute ontology independent layers Semantics is Natural-language and Limit independence independent of social meaning depend on claim to stipulated interpretation use, context, and formal semantics; model communal practices social semantics as stabilized interpretive practice Representation merely Diagrams, notation, and Allow representation exposes prior semantics interaction can and interpretation to restructure categories, revise effective inference, and later semantic state and semantic commitments ontology Information is a Shannon information Type every information neutral middle layer excludes meaning; claim; do not place one semantic information generic information theories disagree on layer in the truth and relevance architecture Behavior reveals Behavior is multiply Require interventions, interpretation realizable and process measures, and confounded by skill, competing-model tests goals, incentives, environment, and chance Software architecture Layered architectures Use architecture as already proves the are engineering evidence of practical model decompositions, often separability, not leaky and metaphysical proof application-specific Computers possess Searle and Remain neutral on intrinsic semantics derived-intentionality intrinsic machine arguments deny that understanding; syntax alone suffices; distinguish formal causal and functional semantics from theories offer phenomenal or alternatives intentional meaning ------------------------------------------------------------------------ # 10. Threats to Validity Terminological heterogeneity is the principal threat. \'Interpretation\' names a mathematical assignment in logic and a cognitive or cultural process elsewhere. \'Ontology\' names both reality-directed inquiry and engineered artifacts. The synthesis controls this by defining roles rather than asserting lexical identity. Formal and empirical results operate at different levels. A semantics-preservation theorem establishes equivalence under stipulated observations; it does not establish equal user understanding. Behavioral studies show effects under particular tasks and populations; they do not establish universal semantic mechanisms. The review is cross-disciplinary rather than exhaustive. Hermeneutics, phenomenology, enactivism, and social theory contain richer accounts of interpretation than can be formalized here. Their omission would bias the framework toward formalism, so the model explicitly permits socially stabilized and enacted semantics while refusing to treat them as computationally complete. The architecture may be too general to predict behavior without domain-specific mechanisms. This is intentional: it is a conceptual bridge and diagnostic framework, not a complete cognitive theory. Its empirical value depends on whether it supports clearer hypotheses, transformation analyses, and falsification tests than undifferentiated language does. # 11. Discussion The distinctions are not inventions. Philosophical ontology, model-theoretic semantics, semiotic representation, and interpretive practice have long been separated in their home disciplines. Computer science adds unusually sharp demonstrations: a program\'s syntax, denotation, operational behavior, intermediate representation, compiled implementation, and user-facing presentation can be related by proofs without being identical. Ontology engineering further separates a domain commitment from a representation language and from application data. What is missing is not another layer but a shared account of how the roles compose. The proposed relational architecture supplies that account conservatively. Meaningfulness is not located in the ontology, semantic state, representation, interpreter, or behavior alone. It arises when representational vehicles are governed by semantic relations grounded or stabilized within a practice and successfully constrain inference or action concerning a target. Formal systems can instantiate this relation by stipulation and proof; human meaning adds competence, history, convention, embodiment, and purpose. For later work on semantic invariance, the result is precise. What may remain invariant is never \'meaning\' without qualification. Candidate invariants include ontological commitment, denotation, truth conditions, inferential consequences, operational behavior, recoverable task information, interpreted belief, or action outcome. Each requires a declared semantics, context, observer class, admissible transformation, and tolerance. Projection analysis should therefore state which of these is claimed to remain invariant and which may change. # 12. Conclusion Ontology, semantics, representation, interpretation, and behavior can be organized into a coherent computational theory without contradicting existing philosophy and computer science. The evidence does not support a strict hierarchy or a universal one-way pipeline. It supports a relational architecture in which domain commitments constrain semantic assignments; projections realize selected aspects of states and semantics as representations; interpreters apply or construct significance under context; and behavior emerges through goals, capabilities, environment, and feedback. The distinctions are already substantially established, but under incompatible vocabularies and levels of analysis. A genuinely new primitive is not warranted. A cross-disciplinary synthesis is warranted because it prevents category errors and supplies a common method for analyzing invariance, transformation, epistemic access, and behavior. The central theoretical constraint is: no computational artifact is meaningful solely by virtue of its physical form, and no observed behavior uniquely determines the semantics or interpretation that produced it. # 13. Required Artifacts ## A. Canonical Definitions ----------------------------------------------------------------------- **Concept** **Canonical definition** ----------------------------------- ----------------------------------- Ontology A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain; in computation, an explicit formal specification approximating a shared conceptualization. Semantic state The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state. Information A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, or use. Representation A materially or formally realized vehicle that provides selective access to a declared target under a mapping and interpretive practice. Interpretation The application or construction of semantic relations by an interpreting system under context, competence, history, and purpose. Projection A declared transformation from a target description or state to an accessible representational form, specifying preservation, transformation, omission, introduction, operations, assumptions, uses, and failure conditions. ----------------------------------------------------------------------- ## B. Relationship Diagram The diagram is relational rather than strictly layered: ----------------------------------------------------------------------------------------------------------------------------------------------------- **Constraint / **Domain commitments **Semantic assignment S** **Projection **Representation **Interpretation I** **Behavior B** feedback** O** P** R** -------------- -------------------- ------------------------- -------------- ------------------ -------------------- -------------------------------- Forward role Defines admissible Assigns content/behavior Selects and Exposes vehicle Constructs/applies Produces situated action domain transforms significance Primary input Inquiry and practice O plus expressions/states X/S plus use Projection output R plus Interpreted state plus contract context/history goals/capabilities/environment Feedback Revised by Revised by Revised by Redesigned after Learns from outcomes Changes environment and future received anomalies/practice interpretation/evidence failures use evidence ----------------------------------------------------------------------------------------------------------------------------------------------------- ## C. Transformation Matrix Table 7 is the reusable transformation matrix. Its rule is that invariance must be typed and tested independently for ontology, formal semantics, information, representation, interpretation, and behavior. ## D. Cross-Disciplinary Vocabulary -------------------------------------------------------------------------------------------------------------------- **Neutral role **Philosophy / **AI / knowledge **Programming languages** **Linguistics / **HCI / term** logic** representation** semiotics** cognitive science** ------------------ ----------------- ------------------ -------------------------- ----------------- --------------- Domain commitments Ontology; Domain ontology; Types, values, stores, Discourse Task/world ontological TBox event domains ontology; model commitment referents Semantic Interpretation; Model theory; Denotational/operational Reference; truth Intended system assignment satisfaction entailment semantics conditions; meaning; signification conceptual model Representational Sentence, model, Knowledge graph, Syntax, AST, IR, bytecode Signifier, Display, vehicle symbol assertions, utterance, artifact, embedding diagram interface state Interpretive Understanding; Reasoning or Evaluation (formal) or Pragmatic Sense-making, process hermeneutic grounding process programmer comprehension interpretation; recognition, uptake semiosis mental model formation Behavioral Action or speech Decision, plan, Execution trace and output Response and Interaction realization act policy coordination sequence, choice, performance -------------------------------------------------------------------------------------------------------------------- ## E. Open Problems - Grounding: under what causal, functional, biological, or social conditions does formal semantics become intrinsic or non-derived meaning, if ever? - Semantic-state identity: which equivalence relation should govern claims that semantic state persists across languages, modalities, or implementations? - Interpretation measurement: how can competing interpretations be inferred without treating task success as equivalent understanding? - Ontology revision: how should frameworks represent cases where new representations alter the categories through which the target is understood? - Distributed interpretation: what is the correct unit when meaning is stabilized across people, artifacts, institutions, and computational agents? - Plural semantics: how should one system support multiple legitimate semantics or stakeholder interpretations without collapsing into ambiguity? - Machine-generated representations: how can provenance, intended use, and semantic commitments be recovered when no human authored a stable codebook? - Behavioral equivalence: what interventions distinguish shared semantic competence from policy imitation or coincidentally equivalent outcomes? # References Bar-Hillel, Y., & Carnap, R. (1953). Semantic information. British Journal for the Philosophy of Science, 4, 147-157. Borst, W. N. (1997). Construction of Engineering Ontologies for Knowledge Sharing and Reuse. University of Twente. Dretske, F. I. (1981). Knowledge and the Flow of Information. MIT Press. Floridi, L. (2004). Outline of a theory of strongly semantic information. Minds and Machines, 14, 197-221. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin. Grice, H. P. (1957). Meaning. Philosophical Review, 66, 377-388. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5, 199-220. Guarino, N. (1998). Formal ontology and information systems. In Proceedings of FOIS \'98, 3-15. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Kolchinsky, A., & Wolpert, D. H. (2018). Semantic information, autonomous agency, and nonequilibrium statistical physics. Interface Focus, 8(6). Morris, C. W. (1938). Foundations of the Theory of Signs. University of Chicago Press. Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19, 113-126. Peirce, C. S. (1931-1958). Collected Papers of Charles Sanders Peirce. Harvard University Press. Plotkin, G. D. (1981/2004). A structural approach to operational semantics. Journal of Logic and Algebraic Programming, 60-61, 17-139. Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3, 417-457. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379-423, 623-656. Scott, D., & Strachey, C. (1971). Toward a Mathematical Semantics for Computer Languages. Oxford University Computing Laboratory PRG-6. Tarski, A. (1933/1956). The concept of truth in formalized languages. In Logic, Semantics, Metamathematics. Oxford University Press. W3C. (2012). OWL 2 Web Ontology Language: Structural Specification and Functional-Style Syntax, Second Edition. Wittgenstein, L. (1953). Philosophical Investigations. Blackwell. Zhang, J., & Norman, D. A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18, 87-122. ======================================================================== ## FILE: docs/02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.md (912 lines, 45.8 KiB) ======================================================================== **Opportunity, Affordance, and Action Availability** *Toward a Formal Account of What an Agent Can Perceive, Believe, and Do* Cross-disciplinary research paper # Abstract Action availability is represented differently across ecological psychology, human--computer interaction, decision theory, control, reinforcement learning, planning, formal methods, and computer security. These traditions distinguish real possibilities for action, actions enabled in a state, authorized operations, reachable outcomes, perceptually indicated operations, believed possibilities, selected acts, attempted executions, successful transitions, and recovery. No single established construct captures all of these dimensions without changing its inherited meaning. Ecological affordance is relational but does not by itself encode authority, formal state enablement, interface exposure, explicit signaling, belief, execution success, or reversibility. Action-space and choice-set formalisms precisely encode alternatives but usually abstract away their epistemic presentation. Authorization models separate authority from technical capability, while transition systems and control theory distinguish enabled actions and reachable states. HCI separates physical or functional possibilities from signifiers, discoverability, and learned interpretation. This paper concludes that a cross-disciplinary opportunity model is justified, but opportunity is not a new primitive. It is an analytical coordination role over established typed relations. The proposed model represents each candidate action by system-relative feasibility, permission, state enablement, reachability, projection exposure, signaling, agent-relative belief, expected consequences, selection, execution, success, reversibility, and uncertainty. The framework is formalizable as linked predicates over a transition system, authorization relation, projection mapping, observation model, and agent belief state. It provides comparison rules for semantically equivalent projections without implying behavioral equivalence. Six hypotheses are operationalized, and reusable vocabulary, matrices, contracts, comparison protocols, and evidence maps are supplied. # 1. Problem Statement Computational environments frequently support actions that are hidden, display controls that are currently disabled, imply operations they cannot perform, or expose equivalent operations differently across modalities. Treating all such cases as "affordances" obscures important distinctions. A technically valid operation may be prohibited by policy. A permitted operation may not be enabled in the current state. An enabled operation may be absent from the current projection. An exposed operation may not be signaled. A signal may be perceived but not interpreted as actionable. An attempted operation may fail, and a successful transition may still fail to achieve the agent's intended outcome. The explanatory problem is therefore not merely to enumerate actions. It is to state which action relation is being claimed, relative to which system state, authority, projection, agent, task, and time. The central question is how action opportunities should be represented, measured, and compared across projections while preserving distinctions among system-relative availability, epistemic access, belief, choice, execution, outcome, and recovery. # 2. Literature Review Method The review used a concept-centered comparative method. Primary and foundational sources were prioritized where available: Gibson's ecological account of affordance; Norman's distinction between affordances and signifiers; Gaver's technology-affordance analysis; formal transition-system notions of enabled action and reachability; Markov decision-process and options formalisms; control-theoretic controllability; planning operators and preconditions; access-control models; and empirical HCI work on discoverability, feedback, and error recovery. Secondary sources were used only to locate terminology or identify disputes. The analysis proceeded in four stages. First, each tradition's explanandum and formal commitments were identified. Second, candidate opportunity distinctions were tested for logical independence using counterexamples. Third, the distinctions were mapped to existing terminology to avoid unnecessary invention. Fourth, the resulting model was evaluated against six falsification conditions: theoretical redundancy, measurement failure, lack of predictive gain, disappearance of projection effects under controls, excessive context dependence, and existence of a single complete formalism. # 3. Affordance Traditions Gibson introduced affordance as what an environment offers an animal, emphasizing complementarity between animal and environment rather than a property located exclusively in either. On this account, an affordance can exist whether or not it is currently noticed, because it is grounded in the relation between environmental structure and the actor's effectivities. Perception concerns information specifying that relation. Successful action is not required for the affordance to exist, although empirical affordance research often evaluates perceptual calibration by comparing judgments with action limits. HCI adopted and transformed the term. Norman initially used perceived affordance to emphasize what users believe can be done, then later separated affordances from signifiers: the action possibility is one matter; the perceptible indication of where or how to act is another. Gaver distinguished perceptible, hidden, false, and correct affordances, revealing a two-dimensional space between actual action possibility and perceptual information. Hartson further divided physical, cognitive, sensory, and functional affordances, but this expands "affordance" toward a taxonomy of interaction support rather than preserving Gibson's narrower ecological relation. The literature therefore contains several non-equivalent affordance traditions: • Ecological affordance: a relation between actor effectivities and environmental properties that makes an action possible.\ • Perceived affordance: an agent's perception or belief that an action is possible.\ • Signifier: perceivable evidence indicating an operation, location, or manner of action.\ • Technological or functional affordance: a designed system's support for a class of action or use.\ • Social affordance: possibilities for social action structured by other agents, conventions, or institutions.\ • Learned or cultural affordance: action possibilities whose detection or uptake depends on acquired practices. These uses should not be collapsed. Ecological affordance is strongest for relational physical possibility; signifier is strongest for perceptual indication; perceived affordance and learned affordance address agent-relative interpretation; functional affordance often approximates system capability. None alone supplies authority, formal reachability, execution success, or recovery. # 4. Action-Set and Choice-Set Traditions Decision theory and economics represent alternatives through feasible sets or choice sets. These specify options available for selection under constraints. Game theory uses action sets or strategy sets, often indexed by player and information state. Reinforcement learning uses an action set A, commonly with a state-dependent subset A(s), and a policy mapping states or beliefs to action distributions. The options framework adds temporally extended actions with initiation sets, internal policies, and termination conditions. Planning formalisms represent operators with preconditions and effects. Formal transition systems define an action as enabled in a state when a corresponding transition exists. Control theory distinguishes admissible controls and reachable states. Robotics often uses affordance models to prune actions by predicting whether an action is feasible or useful in a state. These formalisms provide exact answers to different questions. A state-dependent action set identifies primitive alternatives available to a model. A choice set describes alternatives offered to a decision-maker. An enabled action is one whose preconditions hold. Reachability concerns whether a target state can be attained by a path, not whether a single action is currently executable. An option is a temporally extended policy, not simply any opportunity. A controllable input is an admissible intervention under a system model. A planning operator is a symbolic transition schema. These concepts are compatible but not equivalent. # 5. Capability, Permission, and Reachability Capability, permission, and reachability must remain separate. Capability has two established senses. In ordinary agent modeling, it denotes an agent's ability or resources to perform an action. In capability-based security, it is an unforgeable token of authority naming an object and associated rights. The latter is not equivalent to physical or computational ability. To avoid ambiguity, the present framework uses effective capability for the conjunction of required agent and system capacities, and authority capability only when referring to security tokens. Permission is normative or institutional. Access-control systems define whether a subject is authorized to perform an operation on an object under a policy, role, attributes, and context. A system may be technically able to execute a prohibited action; prohibition does not make the transition physically or computationally impossible. State enablement is local. An action is enabled when its preconditions hold in the current state. Reachability is path-relative. An outcome is reachable if there exists an admissible sequence from the current state to that outcome. An action can be permitted yet disabled, enabled yet lead nowhere useful, or currently disabled while its outcome remains reachable through an alternative sequence. This yields four system-relative relations: 1\. Domain-valid: the operation belongs to the declared domain model.\ 2. Effective-capable: the agent-system coupling has the capacities required for execution.\ 3. Permitted: policy authorizes the operation.\ 4. Enabled: the operation's current-state preconditions hold. Reachability is then defined over sequences of enabled and permitted transitions, with any safety, resource, and temporal constraints stated explicitly. # 6. Discoverability, Signaling, and Belief Exposure, signaling, discoverability, and belief describe different epistemic relations. Exposure means that the current projection provides an executable access path to an operation. A menu item, command syntax, API endpoint, gesture, or conversational intent can expose an operation. Exposure does not require conspicuous indication: a keyboard shortcut may be exposed but hidden from a novice. Signaling means that perceivable structure indicates an operation, its locus, or its expected manner of use. Labels, shape, contrast, prompts, examples, disabled states, documentation, and feedback can signal. A signal can be false when it suggests an unavailable operation. Discoverability is an empirical relation among projection, agent, task, context, and search process. It concerns whether and how an agent can find an operation or relation without already knowing the access path. Discoverability should be measured through controlled search, recognition, recall, or guided exploration---not inferred from visibility alone. Believed action is an action the agent represents as available with some confidence and expected consequence. Belief is latent. It requires elicitation, prediction, confidence reports, recognition tests, or model-based inference with acknowledged uncertainty. Selection is observable choice among represented alternatives. Execution is an observable attempt. Success is a system-relative transition criterion or task-relative outcome criterion; these must be distinguished. # 7. Candidate Typed Opportunity Model The evidence supports a typed opportunity model, not opportunity as a primitive natural property. "Opportunity" is retained as an umbrella analytical role because no single inherited construct coordinates domain validity, capability, authority, state enablement, reachability, exposure, signaling, belief, outcome expectation, and recovery without semantic overextension. Let a computational interaction model be: M = ⟨S, A, T, C, P, Π, Σ, O, B, G, R⟩ where S is the set of system states; A is the action vocabulary; T ⊆ S × A × S is the transition relation or probabilistic kernel; C(a, x, s) is effective capability for agent x; P(a, x, s) is permission; Π maps system state and action structure into a projection; Σ is the signaling relation realized by the projection; O is the observation model available to the agent; Bx is the agent's belief distribution over states, actions, and consequences; G is the task or goal specification; and R describes recovery and reversibility relations. For agent x at time t in state s under projection π, the opportunity profile is not one set but a family of typed sets and relations: D(s): domain-valid actions.\ Cₓ(s): effectively capable actions.\ Pₓ(s): permitted actions.\ E(s): enabled actions.\ Xπ(s): exposed actions.\ Sπ,x(s): signaled actions detectable by x.\ Bₓ(s): actions believed available by x, with confidence.\ Kₓ(s,a): expected consequence distribution.\ L(s,G): reachable outcome set under admissible sequences.\ V(s,a): reversibility or recoverability relation.\ U: uncertainty attached to system state, observer state, and inferred variables. Selected, executed, and successful are event predicates over a trace rather than standing opportunity sets. This avoids treating behavior as part of availability. The currently executable authorized set is:\ A_exec(x,s) = D(s) ∩ Cₓ(s) ∩ Pₓ(s) ∩ E(s). The projection-accessible set is:\ A_access(x,s,π) = A_exec(x,s) ∩ Xπ(s). The signaled executable set is:\ A_signal(x,s,π) = A_access(x,s,π) ∩ Sπ,x(s). The believed executable set is not assumed to be a subset of A_exec:\ A_belief(x,s,π) = Bₓ(s). False positive belief consists of Bₓ(s) \\ A_exec(x,s); hidden opportunity consists of A_exec(x,s) \\ Bₓ(s). This asymmetry is central to conversational overclaim, expert knowledge, and misleading controls. # 8. Formal Representations No single formalism covers every distinction without extension. Labeled transition systems are best for state, enabled action, trace, and reachability. Planning domains add preconditions, effects, and goals. MDPs and POMDPs add uncertainty, value, policies, and belief states. Options add temporally extended action. Control models formalize admissible inputs, dynamics, and controllability. Access-control matrices and policy languages formalize authorization. Observation models formalize partial access to state. HCI and ecological models contribute signaling, perception, effectivities, and learned interpretation. Reversibility requires inverse transitions, compensating actions, checkpoints, or probabilistic recoverability. The recommended architecture is layered but linked: Domain and transition layer: D, S, A, T.\ Capability and authority layer: C, P.\ Projection layer: Π, exposure X, signaling Σ.\ Epistemic layer: O, belief B, expected consequences K.\ Policy layer: goals G and action-selection policy μ.\ Trace layer: selection, execution, transition, outcome, feedback.\ Recovery layer: V and repair paths. The layers should not be treated as a one-way causal chain. Projection can alter actual feasibility when it gates operations, not merely epistemic access. Execution changes state and therefore subsequent opportunity. Feedback changes beliefs, skill, and policies. Authority can change dynamically. Social action can alter policy or projection. The model is therefore a coupled state-transition system with feedback. # 9. Empirical Measurement System-relative variables can often be observed or computed directly: domain membership, permission decision, precondition satisfaction, transition occurrence, reachable states under a declared model, exposure path, and recorded execution. Signaling strength, belief, expected consequence, confidence, and perceived reversibility require empirical measurement or inference. Recommended measures include: Action discovery: proportion finding an operation; time to first correct identification; search path length; number of representation regions inspected; unaided versus prompted discovery. Awareness and belief: recognition of available actions; free recall; prediction of whether an operation will execute; confidence-calibrated availability judgments; precision and recall of the believed action set against A_exec. Selection: conditional probability of selection given belief and exposure; choice latency; switching rate; strategy entropy. Unavailable-action attempts: frequency and type of actions executed outside E, P, or D; whether the mismatch was signaled; recovery after rejection. Recovery: time to identify corrective action; repair success; number of irreversible or escalating transitions; use of undo, backtracking, help, or alternative routes. Transfer: change in believed action precision, discovery time, and strategy use across projections or tasks, controlling for exposure history. Reversibility judgment: predicted recoverability, confidence, and calibration against the actual recovery graph. Direct observations should be separated from latent interpretations. A pause is not direct evidence of hesitation; it is a duration requiring alternative explanations. An unselected action is not evidence of unawareness. Task completion is not evidence of equal opportunity. Belief claims require either explicit reports or a validated latent-variable model. # 10. Comparative Cases Case 1 --- Hidden but feasible action. A system supports an API operation that is permitted, enabled, and executable, while the GUI omits it. The action is in A_exec but not X_GUI. For an expert using documentation it may be signaled and believed through another projection; for a GUI-only novice it is hidden. Projection changes epistemic and access structure, not the underlying transition relation. Case 2 --- Visible but unavailable action. A disabled control is exposed as a representational object and may signal a future or conditional operation, but it is not currently executable. It is not a current action opportunity under A_exec. It is a signifier of a domain-valid action whose enablement condition fails. This can improve learnability if the condition is interpretable, or create false belief if the reason is opaque. Case 3 --- Conversational overclaim. A dialogue system states that it can delete an account although no authorized backend operation exists. The action is signaled and may enter the user's believed set but is absent from D, P, E, or X at the execution layer. This is a false-positive opportunity claim. The model predicts elevated failed attempts, trust calibration errors, and inappropriate planning. Case 4 --- Accessibility substitution. A single operation is exposed visually, auditorily, and tactually. Domain validity, permission, and transition semantics may remain invariant, while signaling latency, sequence, spatial comparability, memory demand, error detectability, and recovery differ. Equal task completion does not establish equivalent discovery or effort. Modality-specific observer assumptions must be declared. Case 5 --- Expert and novice. The projection exposes the same executable operations. The system-relative sets D, P, E, and X are equal. Signaling detectability and believed action sets differ because conventions, vocabulary, and procedural knowledge differ. Training can change B and policy μ without changing T or X. Case 6 --- Policy and authorization. A data-export operation is semantically valid, technically executable, and visible, but the user's role is denied. Capability and exposure are present; permission is absent. Attempts may be blocked before transition. The correct explanation is authorization, not lack of affordance or reachability. # 11. Operationalized Hypotheses ## H1 --- Signaling effect Exposure: manipulation of signifier presence, specificity, or state indication while executable action sets remain fixed. Outcome: unaided discovery rate, discovery time, and conditional selection. Controls: layout, motor distance, latency, task value, familiarity, operation order. Manipulation check: recognition of the cue and its intended referent. Exclusions: prior knowledge of hidden shortcut where it defeats manipulation; inaccessible modality. Analysis: multilevel logistic model for discovery and survival or accelerated-failure-time model for latency. Falsification: no practically meaningful signaling effect with confidence interval excluding the preregistered minimum. ## H2 --- Belief mediation Exposure: projection exposure and signaling condition. Mediator: preregistered availability-belief score measured before selection. Outcome: selection and correct execution. Controls: task value, skill, motor cost, confidence response bias, prior exposure. Manipulation check: exposure and signal detection. Exclusions: belief measured after outcome feedback. Analysis: causal mediation with measurement-error model and temporal ordering. Falsification: exposure affects selection without a reproducible indirect effect through measured belief, or belief lacks predictive validity. ## H3 --- Opportunity inequivalence Exposure: two semantically equivalent projections with identical operation semantics and task outcomes. Outcome: typed opportunity distance across exposure, signaling, belief precision/recall, path cost, recovery visibility, and auditability. Controls: state, authority, device performance, content, task, training. Manipulation check: semantic and reachable-outcome equivalence. Exclusions: projections that change backend permissions or transitions unintentionally. Analysis: equivalence/non-equivalence tests by dimension. Falsification: all preregistered dimensions meet equivalence bounds. ## H4 --- Training effect Exposure: structured training versus control under a fixed projection. Outcomes: believed-action precision/recall, discovery time, strategy diversity, and transfer. Moderator: prior expertise. Controls: repetition, feedback, task difficulty, motivation. Manipulation check: knowledge test without execution cues. Exclusions: system or projection changes during study. Analysis: mixed-effects longitudinal model. Falsification: training produces no durable or transferable change beyond repetition. ## H5 --- Recovery effect Exposure: recovery actions exposed/signaled versus hidden or ambiguous, crossed with actual reversibility. Outcomes: error detection, repair initiation, successful recovery, escalation, perceived safety. Mediators: believed recovery set and perceived reversibility. Controls: error severity, time pressure, prior error experience, feedback latency. Manipulation check: recognition of recovery cue. Exclusions: failures with external irreversible consequences not represented in the model. Analysis: multilevel event-history and mediation models. Falsification: recovery support does not alter repair behavior or measured belief under adequate power. ## H6 --- Opportunity model gain Exposure: observational or experimental dataset spanning projections, states, permissions, and expertise. Outcome: held-out prediction of discovery, selection, execution failure, success, and recovery. Predictors: baseline state, task, projection label, history, and action logs versus baseline plus typed opportunity variables. Controls: leakage, model capacity, participant clustering, temporal drift. Manipulation check: reliability of each typed variable. Exclusions: variables derived from future outcomes. Analysis: nested out-of-sample comparison using log loss, calibration, and preregistered minimum gain. Falsification: no robust incremental predictive or explanatory gain. # 12. Falsification Tests The framework should be narrowed or rejected under the following evidence. 1\. Affordance sufficiency. If a stable, operational ecological-affordance formalism can encode authority, state enablement, exposure, signaling, agent belief, expected consequence, execution success, and reversibility without redefining affordance beyond recognition, the umbrella model is redundant. Current evidence does not show this. 2\. Action-space sufficiency. If state-dependent action sets plus observation models and policies explain projection and belief effects without loss, the opportunity vocabulary can be reduced to those components. This remains a serious alternative. The proposed model therefore claims organizational and comparative value, not a new causal substance. 3\. Measurement failure. If believed and signaled sets cannot be estimated with acceptable reliability or predictive validity, they should not be treated as stable measured constructs. They may remain trial-specific latent variables. 4\. No incremental gain. H6 is falsified if typed variables do not improve out-of-sample prediction or explanation over state, task, projection label, prior experience, and action logs. 5\. Projection null. H1 and H3 are weakened if signaling and exposure manipulations have no effect after familiarity, task, motor cost, latency, and implementation quality are controlled. 6\. Context non-comparability. The comparison protocol fails if opportunity differences cannot be stated under common target, task, observer, and tolerance conditions. In that case comparison must remain local rather than general. 7\. Formal unification. If one established formalism already supports every required relation with standard terminology and empirical mappings, the cross-disciplinary synthesis should adopt that formalism rather than retain "opportunity." # 13. Threats to Validity Conceptual breadth is the principal threat. Terms such as affordance, capability, option, and information have discipline-specific meanings, and normalization can erase productive differences. The paper therefore retains typed definitions rather than declaring terminological identity. Formal models simplify human action. Belief sets, goals, and expected consequences may be distributed, unstable, socially negotiated, or non-propositional. Treating them as variables is an analytical commitment, not a claim that cognition literally stores enumerated sets. Reachability and reversibility depend on model completeness. Hidden external state, asynchronous effects, institutional consequences, and irreversible social outcomes can make computed recovery misleading. Empirical identification is difficult. Exposure, signaling, motor cost, familiarity, and implementation quality often covary. Mediation analysis of belief is vulnerable to measurement error and temporal ordering. Demographic categories should not substitute for measured language, experience, perceptual access, training, or situated constraints. The framework is strongest for declared computational tasks with identifiable operations and state transitions. It is weaker for open-ended creative, social, or interpretive activities in which action vocabularies and goals emerge during activity. # 14. Implications for Interaction Research The model supplies the missing bridge between representation and behavior without claiming that representation determines action. Projection contributes exposure and signals; observation and prior experience support interpretation; interpretation updates beliefs and expected consequences; policy selects among believed alternatives; execution is filtered by capability, permission, and enablement; outcomes and feedback alter later state, belief, and skill. Opportunity therefore functions primarily as a structured descriptive and mediating construct. It describes the typed relations that condition action selection. Some components can mediate projection effects---particularly belief and expected consequences---while others moderate them, including permission, capability, task, and expertise. The umbrella term itself is not a causal variable unless operationalized through its components. For cross-projection comparison, semantic equivalence should be established independently. Two projections can preserve the same operation semantics and reachable task outcomes while differing in exposure, signaling, belief calibration, recovery visibility, sequence cost, and auditability. Such projections are semantically equivalent under one contract but opportunity-inequivalent under another. # 15. Conclusion The evidence supports determination 3: a cross-disciplinary opportunity model is justified, but opportunity is not a new primitive. Existing traditions already supply the constituent concepts. Ecological psychology supplies relational action possibility; HCI supplies signifiers, discoverability, and perceived availability; formal methods and planning supply enabled actions and reachability; control supplies admissible interventions and controllability; decision theory and reinforcement learning supply action sets, beliefs, policies, options, and expected consequences; access control supplies permission and authority; error-recovery research supplies reversibility and repair. None is individually complete for comparing what computational projections make feasible, accessible, apparent, believed, executable, and recoverable. The warranted contribution is therefore a typed taxonomy and integration contract. Opportunity should denote the coordinated profile of established relations under declared system, projection, agent, task, and temporal conditions. It should not replace affordance, action set, permission, reachability, signifier, belief, policy, or reversibility. Its scientific value depends on measurable components, explicit uncertainty, comparative prediction, and demonstrated incremental explanatory gain. # 16. Reusable Artifacts ## A. Canonical Vocabulary ----------------------------------------------------------------------- Term Canonical definition Boundary ----------------------- ----------------------- ----------------------- Affordance A relation between Agent--environment environmental relative; not identical properties and an to signal, belief, agent's effectivities permission, or success. that makes a class of action possible; perception is not constitutive in the Gibsonian sense. Action possibility A minimally specified Use only when the relation under which an relevant action can occur given modality---physical, relevant capacities and computational, conditions. institutional---is declared. Capability The effective capacity Do not confuse with or resources required permission or with a for an agent-system security capability coupling to execute an token. action. Permission Authorization under a Normative; an policy, role, rule, or impermissible action institutional condition may remain technically for a subject to possible. perform an operation. Reachability Existence of an Path-relative, admissible sequence of constraint-relative, transitions from a and model-relative. current state to a target state or set. Exposure Provision by the An exposed operation current projection of may be hidden, poorly an executable access signaled, or unknown. path to an operation. Signaling Perceivable indication May be true, of an operation, its incomplete, ambiguous, locus, manner, or false. condition, or consequence. Discoverability Empirical probability Task-, observer-, and process by which an context-, and agent can find an time-relative. operation or relation under declared conditions. Believed action An action represented Latent; measured by by an agent as elicitation or available, with an validated inference. associated confidence and expected consequence. Opportunity An umbrella analytical Not a new primitive and profile coordinating not synonymous with typed affordance or action action-availability set. relations under declared system, agent, projection, task, and time conditions. Reversibility The degree to which May be exact, consequences of an compensatory, partial, action can be undone, probabilistic, or compensated, repaired, unavailable. or safely explored under declared costs and constraints. ----------------------------------------------------------------------- ## B. Opportunity Matrix ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Action Domain-valid Capable Permitted Enabled Reachable Exposed Signaled Believed Selected Executed Successful Reversible outcome ----------------- -------------- --------- ----------- ---------------- ------------ ---------- ---------- ------------------ -------------- ----------- ------------ ------------ GUI-hidden API Yes Yes Yes Yes Yes No in GUI No in GUI Expert-dependent Context Context Context Usually export Disabled submit Yes Yes Yes No Possibly Visible Yes Often No/attempted Blocked No N/A later only transition Unsupported No/absent No No No No Apparent Yes Possible Possible Attempted No N/A conversational delete Role-prohibited Yes Yes No Policy-blocked No May be May be Possible Possible Blocked No N/A export admissible path ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ## C. Opportunity Contract Projection contract Identity\ • Declared target system, task, agent class, state scope, and comparison time.\ • Projection identifier and modality. System-relative action structure\ • Domain-valid action vocabulary and transition semantics.\ • Effective capability requirements.\ • Permission and authority rules.\ • Current enablement predicates.\ • Reachable outcomes and path constraints.\ • Failure modes and irreversible effects. Projection-relative structure\ • Exposed operations and access paths.\ • Signifiers, labels, conventions, and feedback.\ • Hidden prerequisites and external documentation.\ • Ordering, composition, audit, and recovery support. Observer assumptions\ • Sensory and motor access.\ • Language, conventions, training, and prior exposure.\ • Available assistive technologies.\ • Goal and risk context. Epistemic variables\ • Believed action distribution.\ • Expected consequence distribution.\ • Confidence and uncertainty.\ • Perceived reversibility and cost. Validity\ • Intended use.\ • Metrics and tolerances.\ • Known omissions.\ • Conditions under which comparisons fail. ## D. Opportunity Comparison Protocol Representation comparison protocol 1\. Declare the invariant target: operation semantics, task, initial state distribution, authority policy, and success criterion.\ 2. Verify system equivalence: confirm whether the projections share the same domain-valid, permitted, enabled, and reachable structures. Record any actual gating differences.\ 3. Enumerate projection exposure: identify every operation-access path, required sequence, modality, and prerequisite.\ 4. Code signaling: record perceptible cues, labels, conventions, state indications, feedback, and recovery cues.\ 5. Specify observers: measure relevant experience, language, sensory access, motor access, and training rather than using demographic proxies.\ 6. Measure belief: elicit availability judgments, expected consequences, confidence, and perceived reversibility before execution where possible.\ 7. Observe behavior: discovery, selection, execution, success, error, switching, and recovery.\ 8. Separate claims: classify every result as direct observation, derived system feature, or latent interpretation.\ 9. Compare typed relations: use set precision/recall, discovery curves, path cost, calibrated confidence, outcome distributions, and recovery metrics.\ 10. Test alternatives: control motor cost, latency, familiarity, content, task, implementation quality, and learning.\ 11. State scope: declare contexts and tolerances under which opportunity equivalence or inequivalence is claimed. ## E. Evidence Map ---------------------------------------------------------------------------------------------------------------------------- Inference Direct observation Derived feature Latent Alternatives Falsifying interpretation evidence ------------- ------------------------------------ ------------------------- ---------------- --------------- -------------- Action was Executable path present and testable Projection-to-operation None required Hidden Independent exposed mapping prerequisite; agents cannot inaccessible execute via modality declared path Action was Cue physically/linguistically Cue-operation coding Cue interpreted Cue decorative; Removing cue signaled present as indication ambiguous does not convention change detection and agents deny association Action was Availability judgment, prediction, Belief-set estimate Internal Demand effects; Judgments lack believed confidence availability guessing; reliability or representation memory predictive validity Agent Longer latency or pause Duration relative to Conflict or Reading, motor Latency hesitated baseline uncertainty delay, unchanged distraction under uncertainty manipulation Action was Undo/repair path succeeds Recovery graph and cost Perceived safety Compensation Recovery fails reversible incomplete; or material external effects effects persist Projection Differences in Typed-set comparison Mediated access Motor cost, Effect changed exposure/signaling/belief/recovery effect familiarity, vanishes under opportunity latency controls ---------------------------------------------------------------------------------------------------------------------------- # 17. 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AI & Society, 25, 441--454. Ware, C. (2012). Information Visualization: Perception for Design. Morgan Kaufmann. ISO 9241-11:2018. Ergonomics of human-system interaction---Usability: Definitions and concepts. ======================================================================== ## FILE: docs/02_Research_Papers/07_Interaction/Interaction_Toward_a_General_Theory_of_Interaction.md (923 lines, 39.4 KiB) ======================================================================== **Interaction** *Toward a General Theory of Interaction* Foundational research paper # Contents > Abstract > > 1\. Problem and Method > > 2\. Existing Conceptions of Interaction > > 3\. Reductive Tests > > 4\. Canonical Definition > > 5\. Necessary and Non-Necessary Conditions > > 6\. Interaction Ontology > > 7\. Interaction Primitives and Grammar > > 8\. Interaction Lifecycle > > 9\. Identity and Invariants > > 10\. Interaction Algebra > > 11\. Composition Rules > > 12\. Comparative Cases > > 13\. Evidence and Operationalization > > 14\. Falsification Tests > > 15\. Threats to Validity > > 16\. Conclusion 17\. Reusable Artifacts 18\. References # Abstract Interaction is invoked across human-computer interaction, cybernetics, ecology, cognitive science, communication, control, formal methods, robotics, and multi-agent systems, but these traditions do not share a single definition. Some identify interaction with reciprocal action, some with communication, some with feedback, some with synchronized events, and some with situated meaning-making. This paper tests whether interaction is primitive or reducible to established constructs. It concludes that interaction is not a primitive substance or basic event type. It is a higher-order relation over coupled processes: two or more distinguishable systems interact during an episode when changes in each system\'s possible or actual state trajectory are counterfactually dependent on perturbations transmitted through a coupling relation within a declared boundary and timescale. Reciprocity may be asymmetric, delayed, mediated, probabilistic, or realized across a sequence; simultaneous action, intention, communication, semantic understanding, and visible behavior are not necessary. A single unilateral causal effect is insufficient unless it enters a closed or recurrent dependency structure. Existing fields provide nearly all constituent concepts - action, coupling, feedback, transition, synchronization, communication, coordination, and situated interpretation - but no single theory supplies a cross-domain identity, composition, and comparison framework. The warranted contribution is therefore a minimal synthesis, not a new primitive: a typed interaction ontology, episode lifecycle, compositional grammar, algebraic operators, identity criteria, invariants, interaction contract, and falsification matrix. # 1. Problem and Method The word interaction often performs explanatory work without identifying what kind of phenomenon occurred. In interface research it may mean a sequence of user inputs and system outputs. In cybernetics it can imply feedback. In communication theory it may mean exchange of messages. In ecological psychology it can indicate organism-environment reciprocity. In formal computer science it can mean synchronization or communication between processes. In social theory it may refer to jointly produced order. These uses overlap, but none can be assumed to define the others. The analysis used a cross-disciplinary boundary method. For each tradition, the study identified: (1) the entities allowed to interact; (2) the relation or mechanism linking them; (3) whether reciprocity, intention, communication, observation, or state change is required; (4) the temporal unit; (5) the evidence by which interaction is established; and (6) the formal resources available for identity and composition. Candidate definitions were then tested against counterexamples including passive sensing, unilateral control, delayed feedback, hidden API effects, failed communication, and simultaneous but independent activity. The supplied corpus was used as foundational evidence for ecological, situated, distributed, activity-theoretic, cognitive-engineering, and interaction-design perspectives. The methodological standard followed the Research Canon: concepts were retained only when necessary, definitions were separated from implementations, and major claims were made falsifiable and operationalizable. # 2. Existing Conceptions of Interaction No accepted universal definition exists. The major traditions organize interaction around different explanatory targets. Ecological psychology treats organism and environment as complementary rather than independent explanatory domains. Gibson\'s affordances are possibilities of action relative to an animal-environment system. This supplies relationality but does not by itself define an interaction episode, identity, or composition. Cybernetics organizes control and communication through feedback. Wiener placed messages and responses within circular regulation. Feedback gives a strong mechanism for recurrent interaction, but open-loop influence and one-shot synchronized events show that feedback is not necessary for every interaction token. Systems theory commonly treats interaction as mutual influence among components whose collective behavior is not recoverable from isolated components alone. This supplies dependence and emergence but often leaves interaction boundaries and empirical identity underspecified. Situated action and ethnomethodological approaches reject the view that plans fully determine conduct. Suchman describes successful interaction as collaboratively produced intelligibility responsive to contingencies and others\' actions. This supplies situated accomplishment and interpretive coordination, but it is too restrictive for non-semantic physical and computational interactions. Distributed cognition locates cognitive organization across people, artifacts, and representational media. Hutchins shows that coordinated transformations across a system can constitute the relevant cognitive process. This supports system-level interaction and mediation but makes boundaries a substantive modeling decision. Activity theory places action within object-oriented, tool-mediated, socially organized activity. It captures historical and institutional mediation, yet its unit is often too large for atomic computational interaction. HCI contains multiple theories rather than one definition. Cognitive engineering models user-system exchanges quantitatively; embodied interaction treats meaning as arising through engaged practice; instrumental and generative theories organize design around action and adaptation; computational rationality explains interaction as adaptation under bounds. These theories explain important classes of interaction but are not extensionally equivalent. Communication theory distinguishes transmission from meaning. Shannon\'s mathematical theory explains signal selection and uncertainty without requiring semantic understanding. Speech-act and agent-communication theories add illocutionary force and protocol commitments. Communication is therefore one interaction mechanism, not interaction\'s genus. Control theory defines systems through inputs, states, outputs, and dynamical response. Coupling occurs when one subsystem\'s output enters another\'s dynamics. This gives precise counterfactual and temporal machinery, but interaction cannot be reduced to successful control because uncontrolled perturbation and negotiation also qualify. Formal methods represent interaction through synchronization, shared events, message passing, handshakes, shared variables, or transitions. CCS, CSP, process algebras, labeled transition systems, event structures, and protocol models provide composition and behavioral equivalence. Their strength is formal precision; their limitation is that semantic and social interpretation normally lies outside the transition semantics. Robotics and multi-agent systems treat interaction through sensing, action, communication, coordination, negotiation, and joint task execution. Protocols specify admissible message sequences and roles. These approaches show that interaction may be globally specified but locally enacted, and that composition can fail when local agents cannot realize a global protocol. Philosophy of action distinguishes intentional action from mere movement or event. This blocks a definition of interaction as simply two actions: many interactions include non-agentive components, unintended consequences, or automatic responses. # 3. Reductive Tests Interaction cannot be reduced to action. An action can occur without another system being coupled to it, while an interaction can include passive dynamics, automatic responses, or non-intentional perturbations. Action is attributable to an agent under some theory of agency; interaction concerns dependence among processes. Interaction cannot be reduced to behavior. Behavior is an observed or modeled pattern attributable to a system. Two systems can behave simultaneously without interacting, and a system\'s behavior may be evidence of interaction without constituting the relation itself. Interaction cannot be reduced to communication. Mechanical contact, resource contention, sensorimotor coupling, and shared-state interference can be interactions without messages or shared meaning. Conversely, a transmitted message that produces no uptake may constitute attempted communication but may fail to establish an interaction episode under a causal-dependence criterion. Interaction cannot be reduced to computation. Computation can occur internally without coupling to another system. Some interactions are physical, biological, or social and are not usefully described as computation. Computational interaction is one domain-specific realization. Interaction cannot be reduced to observation. Observation may be unilateral and non-perturbative at the modeled scale. It becomes interaction when sensing changes subsequent trajectories, when measurement perturbs the observed system, or when observation participates in a recurrent loop. Interaction cannot be reduced to a state transition. A state transition can be internal and autonomous. Interaction requires that at least part of a transition\'s occurrence, probability, timing, or reachable consequences depend on another distinguishable system through a coupling. Interaction cannot be reduced to causation in general. A falling rock may cause a mark in soil, but a single one-way causal event does not automatically justify an interaction episode. The term is most useful when the coupling creates reciprocal or recurrent constraint across the participants\' trajectories. Reciprocity need not be equal or immediate; it may be mediated through a shared environment and realized over time. These failures do not establish interaction as metaphysically primitive. They establish it as a non-redundant analytical relation composed from existing notions of system, state, process, coupling, perturbation, constraint, and temporal dependence. # 4. Canonical Definition Interaction episode: a bounded interval in which two or more distinguishable systems are coupled such that perturbations originating in, or mediated by, one system alter the possible or actual state trajectory of at least one other system, and the resulting configuration constrains a later trajectory of an originating or co-participating system. This definition has six commitments. First, interaction is relational. It is not located exclusively in either participant. Second, interaction is processual. It is extended over at least an analytically distinguishable sequence, even when implemented as an apparently atomic synchronization. Third, interaction requires coupling. A pathway must exist through which perturbation, constraint, resource competition, synchronization, signal, or material effect can pass. Fourth, interaction requires counterfactual dependence. Holding relevant background conditions fixed, removing or changing the coupling or participant would change some participant\'s reachable, probable, timed, or actual trajectory. Fifth, interaction requires reciprocal closure at the episode level. The reciprocal effect can be direct, indirect, asymmetric, delayed, probabilistic, or environmentally mediated. A single isolated one-way influence is causation but not yet interaction under the strict definition. Sixth, every interaction claim is boundary- and timescale-relative. What appears unilateral over milliseconds may be reciprocal over seconds; what appears dyadic may be mediated by infrastructure, institutions, or environments when the boundary expands. # 5. Necessary and Non-Necessary Conditions Necessary conditions are: distinguishable participants or subsystems; a coupling relation; at least one transmitted perturbation or constraint; counterfactual effect on a participant trajectory; reciprocal or recurrent closure within the declared episode; and explicit boundary and timescale. Not necessary are: biological agency; conscious intention; semantic content; successful communication; mutual awareness; equality of influence; simultaneous response; visible interface events; goal agreement; positive outcome; or permanent state change. Observable state change is not strictly necessary if the interaction changes transition probabilities, timing, control margins, uncertainty, or reachable possibilities without producing an immediately observed macrostate change. Such claims require stronger evidence than direct transition traces. Interaction may fail. A protocol can deadlock, a conversational repair can collapse, or a control loop can oscillate. Failure does not erase the interaction; it changes its outcome and lifecycle state. # 6. Interaction Ontology The minimal ontology contains established constructs rather than newly coined entities. Participant: a system or subsystem treated as distinguishable for the analysis. State: the variables considered sufficient to characterize a participant at a time and scale. Process: an ordered or partially ordered evolution of state. Boundary: the inclusion rule separating participants, environment, and background conditions. Coupling: a relation through which one participant or shared medium can affect another participant\'s transition structure. Perturbation: a difference propagated through a coupling relation. Constraint: a change in possible, probable, timed, or admissible trajectories. Uptake: incorporation of a perturbation into a participant transition or control process. Uptake need not be semantic. Response: a subsequent transition attributable partly to uptake. Recurrence: return influence through which a response constrains an earlier source, co-participant, or shared coupling configuration. Episode: a bounded segment containing initiation, coupling, uptake, response, and sufficient closure for identity. Trace: a temporally ordered or partially ordered record of observable events and state estimates. Protocol: a rule system constraining admissible interaction traces. Outcome: the episode-relative resulting state, distribution, commitment, or termination condition. Context: background conditions that affect coupling or interpretation but are not modeled as participants in the focal episode. Environment: modeled external dynamics through which participants may be coupled. Invariant: a declared property preserved across an interaction, representation, implementation, or decomposition. # 7. Interaction Primitives and Grammar The theory does not claim metaphysical primitives. It proposes analytical primitives sufficient for representation. A minimal event vocabulary is: bind(p, q, c): establish or activate coupling c between participants p and q.\ emit(p, d): participant p produces perturbation d.\ transmit(c, d): coupling c carries d.\ uptake(q, d): d changes q\'s transition conditions or state.\ respond(q, r): q undergoes or produces response r.\ recur(r, p\|c): r constrains p or the coupling configuration.\ commit(o): an outcome or commitment becomes episode-relevant.\ fail(f): a declared failure condition occurs.\ unbind(c): coupling terminates or becomes inactive. A minimal interaction grammar is: Episode ::= Boundary Initiation CoupledProcess Closure\ CoupledProcess ::= Exchange \| Synchronization \| SharedMedium \| Feedback \| Coordination\ Exchange ::= Emit Transmit Uptake \[Response\]\ Synchronization ::= JointEvent constrained-by Participants\ SharedMedium ::= ParticipantEffect MediumTransition ParticipantUptake\ Feedback ::= Exchange Recurrence+\ Coordination ::= CoupledProcess constrained-by Protocol\ Closure ::= Recurrence \| JointCommitment \| StableTermination \| DeclaredTimeout \| Failure The grammar separates implementation form from interaction identity. A message exchange, button press, physical collision, or shared-memory write may instantiate the same abstract roles while differing in semantics and mechanism. # 8. Interaction Lifecycle 1\. Eligibility: participants, capacities, permissions, and preconditions make coupling possible.\ 2. Initiation: a participant or environmental condition activates a coupling pathway.\ 3. Perturbation: a difference is produced and propagated.\ 4. Uptake: another participant\'s state or transition structure becomes dependent on that difference.\ 5. Response: a consequential transition occurs.\ 6. Recurrence or closure: the response returns influence, establishes a joint commitment, reaches stable termination, times out, or fails.\ 7. Aftereffect: participant states, beliefs, policies, coupling strength, or future opportunities may change. These phases are analytical, not universally sequential. Synchronization can merge initiation, uptake, and response. Distributed interaction can contain concurrent branches. Repeated interaction can overlap aftereffects with the eligibility conditions of later episodes. # 9. Identity and Invariants Interaction identity is not exhausted by event equality. The same interaction may be rendered through different modalities, implementations, or trace granularities. Conversely, superficially identical event sequences may constitute different interactions when participants, semantics, authority, or causal dependencies differ. An interaction identity claim must declare: participants and roles; focal boundary; timescale; coupling topology; relevant state variables; protocol or admissibility conditions; causal or counterfactual dependencies; initiation and closure criteria; and invariants. Strong token identity requires continuity of the same causal episode. Type identity requires equivalence under a declared abstraction. Candidate invariants include: Participant-role invariance: the same abstract roles are preserved despite implementation changes.\ Protocol invariance: admissible ordering and obligation structure are preserved.\ Transition invariance: corresponding actions induce equivalent abstract state changes.\ Causal-structure invariance: the counterfactual dependency graph is preserved.\ Outcome invariance: declared terminal conditions or distributions are preserved.\ Information invariance: selected distinctions available to participants are preserved.\ Opportunity invariance: relevant feasible, permitted, exposed, and recoverable actions are preserved.\ Behavioral invariance: trace distributions remain equivalent under a metric and tolerance. No invariant is universal. Every equivalence claim must name the preserved relation, observer, abstraction, context, and tolerance. # 10. Interaction Algebra Let an interaction type I be represented as a tuple: I = \ where P is a set of participants and roles; S is a structured state space; C is a coupling topology; E is a typed event set; T is a transition or stochastic kernel; R is a recurrence and dependency relation; B specifies boundary and timescale; and K specifies closure conditions and invariants. The following operators are sufficient for a minimal compositional algebra. Sequential composition I ; J: J begins after a closure condition of I and may inherit a mapped state. Parallel composition I \|\| J: episodes proceed concurrently with independent or shared participants. Synchronization I sync_A J: episodes must jointly participate in events from synchronization set A. Choice I + J: one of several admissible episode structures is realized. Iteration I\*: zero or more recurrent instances under a termination rule. Mediation M\[I\]: interaction I is realized through mediator or environment M. Restriction I\\H: selected events or coupling channels are hidden from an observer while remaining causally active. Abstraction alpha(I): implementation events are mapped to a coarser interaction type. Refinement I \<= J: J preserves the declared invariants and allowed behavior of I while adding implementation detail. Interference I bowtie J: concurrent interactions share state or resources such that each changes the other\'s reachable traces. These operators borrow from process algebra, transition systems, and systems theory. The proposed synthesis adds explicit participant roles, episode boundaries, recurrence criteria, and cross-domain invariants. Algebraic laws are conditional rather than universal. Sequential composition is not necessarily commutative; parallel composition may cease to be associative when resource or timing assumptions change; abstraction must preserve declared observables to support equivalence. # 11. Composition Rules Interactions compose only when boundary mappings are valid. A participant in one episode may become an environment, mediator, or internal subsystem in another abstraction. State compatibility: the terminal state distribution of the first episode must satisfy the initial-state assumptions of the second. Role compatibility: inherited participant roles and authority must remain meaningful. Coupling compatibility: channels, shared variables, or physical interfaces must connect without introducing unmodeled transformations. Temporal compatibility: ordering, concurrency, deadlines, and latency assumptions must be satisfiable. Semantic compatibility: where messages or commitments are involved, content interpretations and protocol meanings must align. Invariant compatibility: composition must not silently violate safety, identity, or observational equivalence conditions. Closure discipline: a subinteraction may be incomplete while the containing interaction remains active, but its completion, timeout, cancellation, or compensation must be represented. Composition is therefore not mere concatenation of event logs. It is a constrained construction over state, roles, coupling, time, and invariants. # 12. Comparative Cases Human-human conversation. Participants alternate and overlap utterances, gestures, gaze, repair, and inference. Communication and semantic interpretation are central, but the interaction also includes timing, turn allocation, mutual orientation, and embodied feedback. Identity depends on the evolving joint episode rather than isolated messages. Human-computer interaction. A user action changes system state or presented information; the resulting projection changes the user\'s opportunities, beliefs, or next action. Reciprocity is asymmetric because the computational system need not possess intention. Interaction is established by coupled trajectories, not by anthropomorphic agency. Agent-agent interaction. Agents exchange messages, synchronize on shared state, negotiate, or coordinate through protocols. Interaction can be formally represented as global protocols and local enactments. Failed enactability demonstrates that a global trace specification is not sufficient unless local participants can realize it. API interaction. A client request invokes a service transition, and the response, error, side effect, or timeout changes the client\'s later state or policy. A fire-and-forget request with no later client dependence may be a unilateral invocation; an episode becomes interaction when returned or shared-state effects constrain subsequent behavior. Physical interaction. Two bodies collide, deform, transfer momentum, and alter each other\'s trajectories. There is no required communication or interpretation. Reciprocal physical dependence provides the clearest minimal example. Conversational interaction with a computational agent. Messages are represented as linguistic acts, but the underlying episode also includes model state, tool availability, authorization, latency, and projection. Apparent semantic reciprocity can exceed actual computational capability, so interaction analysis must separate signaled, believed, and feasible transitions. Across all six cases, what remains common is not intention, language, interface, or computation. It is bounded reciprocal constraint through coupling, observable or inferable in participant trajectories. # 13. Evidence and Operationalization Direct evidence includes synchronized event traces, state measurements, messages, control signals, resource changes, and observed transitions. Derived evidence includes reconstructed causal graphs, reachability differences, transfer functions, protocol conformance, and temporal dependencies. Interpretive evidence includes inferred intention, meaning, belief, coordination, and social significance. A minimal empirical test for interaction compares a coupled condition with a suitably matched decoupled or perturbed condition. Evidence should show that changing participant A or coupling C changes B\'s trajectory and that B\'s resulting state or response changes a later trajectory of A, C, or a shared system within the episode boundary. Possible measures include conditional mutual information, intervention effects, transfer entropy, Granger-style temporal dependence, impulse response, synchronization, cross-recurrence, state-transition divergence, protocol trace conformance, and causal model comparison. None alone proves interaction. Statistical dependence without a plausible coupling may be confounding; causal influence without recurrence may be unilateral causation; synchronized traces may share an external driver. For semantic and social interaction, additional evidence may include repair sequences, uptake displays, commitment changes, alignment, or coordinated task transitions. Such evidence should not be generalized to physical or non-semantic interaction. # 14. Falsification Tests The theory should be rejected or narrowed if any of the following is demonstrated. Reduction to transition systems: if standard transition-system semantics can represent participants, coupling, recurrence, episode identity, interpretation boundaries, and cross-domain composition without additional commitments, the proposed ontology adds no explanatory value. Reciprocity failure: if scientific practice consistently classifies one-way causal influence as interaction and no explanatory or predictive gain follows from distinguishing it, reciprocal closure should be removed from the definition. Boundary non-reproducibility: if independent researchers cannot agree on episode boundaries and timescales under explicit rules, interaction identity may be too observer-relative for stable comparison. Counterfactual non-identifiability: if coupled and merely correlated trajectories cannot be distinguished even in principle for relevant domains, interaction cannot support causal explanation there. Composition failure: if the algebra cannot predict or explain properties of composed episodes beyond raw event concatenation, it should be treated as notation rather than theory. Invariant failure: if no useful property can be preserved across implementation-independent representations of interaction, claims of general interaction types should be abandoned. Existing-theory sufficiency: if one established theory provides equivalent vocabulary, ontology, mechanisms, formalization, and empirical predictions across all comparative cases, the synthesis should be replaced by that theory. Predictive null: if interaction-level variables do not improve explanation or prediction over participant-level states, independent causal models, and background context, interaction may be merely descriptive. # 15. Threats to Validity The definition privileges reciprocal constraint and may exclude ordinary language uses such as a person interacting once with a passive artifact. This is deliberate but contestable. The stricter definition seeks explanatory discrimination; broader usage may be appropriate in design practice. Counterfactual dependence is model-relative. Incorrect state variables, hidden common causes, or poorly chosen timescales can create or erase apparent interaction. Reciprocal effects may be too weak or delayed to estimate. The framework combines traditions with incompatible ontological assumptions. Ecological psychology resists internal representational explanations; formal computer science abstracts away material embodiment; social theory treats meaning and accountability as locally accomplished. The synthesis claims a shared structural layer, not theoretical unification of all explanatory levels. Formal composition can obscure situated transformation. Real participants reinterpret protocols, change goals, and alter boundaries. Interaction types should therefore be treated as models with scope conditions, not exhaustive descriptions. The comparative cases are selected to maximize diversity, but they do not establish universality. Biological symbiosis, market interaction, quantum interaction, and institutional interaction may require revisions. # 16. Conclusion Interaction is not a primitive substance, action type, or universal mechanism. Nor is it adequately reducible to action, behavior, communication, computation, observation, state transition, feedback, or causation alone. The literature supports a minimal cross-disciplinary synthesis: interaction is a bounded, temporally organized relation of reciprocal constraint among distinguishable systems through coupling. Its tokens are established by counterfactual dependence in participant trajectories; its types are defined only under declared boundaries, roles, abstractions, and invariants. Communication, synchronization, feedback, coordination, collision, shared-state interference, and situated meaning-making are mechanisms or forms of interaction rather than synonyms. Existing disciplines provide the constituent theory, but no single one provides a complete cross-domain account of identity, composition, invariance, and evidence. The minimum conceptual addition is therefore not a new primitive. It is a shared interaction contract and typed compositional framework that makes existing concepts interoperable and empirically testable. # 17. Reusable Artifacts ## Interaction Taxonomy ----------------------------------------------------------------------- Element Definition / specification ----------------------------------- ----------------------------------- By coupling mechanism physical contact; field or environmental mediation; signal transmission; shared state; resource contention; synchronization; institutional or normative mediation By temporal form atomic synchronization; request-response; feedback loop; recurrent exchange; continuous coupling; asynchronous protocol; episodic coordination By agency non-agentive; unilateral-agentive; dyadic agentive; multi-agent; human-machine; system-environment By semantic status non-semantic; informational; communicative; interpretive; commitment-forming By symmetry symmetric; asymmetric; leader-follower; controller-plant; client-service; many-to-many By outcome successful; failed; partial; deadlocked; oscillatory; compensated; abandoned ----------------------------------------------------------------------- ## Interaction Contract ----------------------------------------------------------------------- Element Definition / specification ----------------------------------- ----------------------------------- Identity interaction type and token identifier; abstraction level Participants entities, roles, capabilities, authority, and inclusion criteria Boundary system/environment partition; timescale; start and closure rules State relevant state variables and uncertainty Coupling channels, shared media, topology, latency, and capacity Preconditions eligibility, permissions, enablement, and initial assumptions Events emission, transmission, uptake, response, recurrence, commitment, failure Transitions deterministic, nondeterministic, or probabilistic state effects Protocol admissible ordering, synchronization, obligations, and timeouts Invariants properties required to remain preserved Evidence direct observations, derived dependencies, inferred interpretations Failure and recovery deadlock, rejection, timeout, compensation, cancellation, rollback Completion stable termination, commitment, goal condition, timeout, or declared truncation ----------------------------------------------------------------------- ## Falsification Matrix ----------------------------------------------------------------------- Claim Contrary evidence and consequence ----------------------------------- ----------------------------------- Interaction is relational Cases where interaction is fully attributable to one participant without coupling -\> Remove relationality or restrict domain Reciprocal closure is necessary Reliable explanatory practice treating isolated one-way influence as interaction -\> Broaden definition to directed causal coupling Counterfactual dependence Matched interventions fail to distinguishes interaction separate interaction from common-cause correlation -\> Limit causal claims to descriptive coordination Interaction types survive No useful invariants across implementation change implementations -\> Abandon general types; retain local episode descriptions Composition adds explanatory value Composed properties equal unconstrained event concatenation -\> Drop algebra; use trace notation only Synthesis is non-redundant One established theory matches all ontology, formal, and empirical requirements -\> Adopt that theory and reject the synthesis ----------------------------------------------------------------------- ## Dependency Graph Ontology -\> state and participant identity -\> coupling -\> opportunity -\> perturbation and uptake -\> interaction episode -\> interpretation and policy -\> behavior -\> evidence and measurement -\> comparison and prediction. ## Interaction Comparison Protocol 1\. Declare the focal boundary, timescale, participants, roles, and state abstraction. 2\. Identify coupling mechanisms and construct a counterfactual decoupled baseline. 3\. Enumerate observable events, hidden state assumptions, and uncertainty. 4\. Test directed influence and reciprocal or recurrent closure. 5\. Identify protocol, semantic, causal, outcome, opportunity, and behavioral invariants separately. 6\. Compare traces only after aligning state abstraction and event granularity. 7\. Control for common causes, shared external drivers, latency, and measurement artifacts. 8\. State whether the claim concerns token identity, type equivalence, refinement, or similarity. 9\. Report failures, deadlocks, timeouts, and recovery as part of the interaction rather than deleting them. 10\. Declare the conditions under which the comparison would be falsified. # 18. References Bateson, G. (1972). Steps to an Ecology of Mind. Chandler. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Lawrence Erlbaum. Clark, H. H. (1996). Using Language. Cambridge University Press. Dourish, P. (2001). Where the Action Is: The Foundations of Embodied Interaction. MIT Press. Engestrom, Y. (1987). Learning by Expanding: An Activity-Theoretical Approach to Developmental Research. Orienta-Konsultit. Ferrando, A., Winikoff, M., Cranefield, S., Dignum, F., & Mascardi, V. (2019). On the enactability of agent interaction protocols: Toward a unified approach. AAMAS. FIPA. (2002). FIPA Agent Communication Language Specifications and Interaction Protocol Specifications. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin. Hoare, C. A. R. (1985). Communicating Sequential Processes. Prentice Hall. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Kendon, A. (1990). Conducting Interaction: Patterns of Behavior in Focused Encounters. Cambridge University Press. Luhmann, N. (1995). Social Systems. Stanford University Press. Maturana, H. R. (2002). Autopoiesis, structural coupling and cognition. Cybernetics & Human Knowing, 9(3-4), 5-34. Mead, G. H. (1934). Mind, Self, and Society. University of Chicago Press. Milner, R. (1980). A Calculus of Communicating Systems. Springer. Milner, R. (1989). Communication and Concurrency. Prentice Hall. Norman, D. A. (2013). The Design of Everyday Things, revised and expanded edition. Basic Books. Oulasvirta, A., Jokinen, J. P. P., & Howes, A. (2022). Computational rationality as a theory of interaction. Proceedings of CHI 2022. Ramadge, P. J., & Wonham, W. M. (1987). Supervisory control of a class of discrete event processes. SIAM Journal on Control and Optimization, 25(1), 206-230. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379-423, 623-656. Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press. Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM, 40(5), 80-91. Wiener, N. (1948). Cybernetics: Or Control and Communication in the Animal and the Machine. MIT Press. Winograd, T., & Flores, F. (1986). Understanding Computers and Cognition. Ablex. ======================================================================== ## FILE: docs/02_Research_Papers/08_Behavior/Behavior_Toward_a_Scientific_Theory_of_Computational_Behavior.md (917 lines, 44.6 KiB) ======================================================================== **Behavior** *Toward a Scientific Theory of Computational Behavior* Cross-disciplinary foundational research paper # Abstract Behavior is indispensable across psychology, ethology, cognitive science, economics, reinforcement learning, cybernetics, robotics, systems theory, human-computer interaction, and philosophy of action, yet the term refers variously to movement, response, output, action, policy, performance, conduct, and organism-environment coordination. This paper asks what constitutes behavior and how it should be represented scientifically without dependence on a particular interface or technology. The review finds no single accepted definition, but it identifies a stable analytical core. Behavior is best treated as a bounded, temporally extended trajectory of observable or instrumentally recoverable changes attributable to a system in relation to its environment. Behavior is not identical to state, because it concerns change or persistence across time; not identical to action, because action normally adds agency, organization, or purposive interpretation; not identical to interaction, because interaction requires reciprocal constraint between distinguishable systems; and not identical to a policy, strategy, intention, or goal, which are explanatory or latent structures rather than observations. Existing theories are sufficient for most component problems but lack a shared evidence-preserving representation spanning human, animal, and artificial systems. The paper therefore proposes a typed trace framework rather than a new behavioral primitive. It separates raw records, detected events, attributed behavioral events, episodes, patterns, actions, strategies, and latent explanations. It supplies a behavior ontology, behavioral grammar, trace model, evidence hierarchy, taxonomy, annotation contract, and falsification criteria. Its central claim is that scientifically useful behavioral representation requires explicit system boundaries, observation functions, temporal segmentation rules, attribution criteria, context, uncertainty, and a prohibition against treating latent explanations as direct observations. # 1. Problem and Scope Computational interaction research frequently treats clicks, commands, gaze shifts, messages, state changes, task completion, and model outputs as behavior. These records are not equivalent. Some are environmental measurements, some are system transitions, some are experimenter-defined events, and some are interpretations of agency, purpose, belief, or strategy. Without a theory of behavior, interaction traces risk becoming collections of implementation-specific events whose explanatory status is unclear. The problem is not solved by defining behavior as whatever a system does. That formulation is too broad to distinguish behavior from internal dynamics, passive displacement, noise, or arbitrary state change. Conversely, limiting behavior to intentional human action excludes organisms, robots, adaptive software, reflexes, omissions, and learned but non-deliberative conduct. A useful account must remain implementation-independent while retaining empirical discipline. The paper evaluates whether established theories already supply a sufficient account. The objective is not a universal metaphysical definition. It is a minimal scientific architecture adequate for representing behavioral evidence across computational interactions. # 2. Method and Standards The review compares explanatory structures rather than recounting disciplinary histories. Primary and foundational works were prioritized: Dewey on the reflex arc; Skinner on operant behavior; Tinbergen on ethological explanation; Rosenblueth, Wiener, and Bigelow on behavioral classification and purpose; Ryle and philosophy of action on dispositions and agency; Newell and Simon on problem-solving protocols; ecological and situated approaches on organism-environment coordination; reinforcement learning on policies and trajectories; and HCI on task performance, action sequences, and interaction logs. For each tradition, the analysis identifies: the entity to which behavior is attributed; the temporal unit; the role of environment; whether purpose or intention is required; the observational basis; the explanatory mechanism; and the treatment of latent variables. Candidate distinctions are retained only when counterexamples show that collapsing them would generate false inferences. This follows the project\'s canon: define vocabulary, separate observation from interpretation, prefer mechanisms, require operationalization and falsifiability, and leave reusable artifacts. # 3. Major Traditions ---------------------------------------------------------------------------------------- **Tradition** **Behavioral object** **Typical **Strength and evidence** limit** ---------------------- ------------------------ ------------------- -------------------- Behaviorism Environmentally related Observable response Strong operational responding; operants and and contingencies discipline; weak on response classes representation, distributed activity, and observer construction. Ethology Species-typical and Behavioral patterns Multilevel individual behavior in explained by explanation; natural context mechanism, segmentation and development, observer dependence function, and remain difficult. phylogeny Ecological psychology Organism-environment Perception-action Avoids isolated coordination relations and stimulus-response affordances units; may underdescribe symbolic and institutional mediation. Cognitive science Performance generated by Tasks, protocols, Mechanistic and information-processing errors, timing, computational mechanisms internal models detail; latent structures can outrun evidence. Situated/distributed Activity organized Coordinated Captures context and cognition across people, trajectories and distribution; system artifacts, and settings representational boundaries become transformations analytically contested. Cybernetics/control Input-output relations, Trajectories, error General across feedback, regulation, signals, stability, natural and goal-directed dynamics control artificial systems; agency and meaning are not intrinsic. Behavioral economics Choices under Selections, Quantitative constraints and response regularity; observed incentives distributions, choice does not revealed uniquely reveal preferences preference or belief. Reinforcement learning Policy-generated Actions, Formal and testable; state-action-reward observations, modeled state/action trajectories rewards, returns, spaces may omit policies situated behavior. Robotics Embodied sensing, Sensorimotor Links behavior to control, and action traces, dynamics; success trajectories, task criteria are outcomes designer-relative. HCI/human factors Human performance in Events, timing, Operationally rich; designed systems errors, workload, logs are often task completion interface-specific and psychologically underdetermined. Philosophy of action Actions, agency, Intentional and Clarifies intention, reasons, attributable action/behavior omissions conduct distinction; less suited to non-agentive or artificial cases. ---------------------------------------------------------------------------------------- # 4. Canonical Distinctions ## 4.1 State, change, and behavior A state is a description of a system at a time or over an interval. Behavior concerns a trajectory, transition pattern, controlled persistence, or temporally organized relation among states. Remaining still can count as behavior when maintaining position is attributable to regulation or policy; mere static existence does not. This means change is not strictly necessary, but temporal organization and counterfactual sensitivity are. Internal state change is not automatically behavior. A memory allocation, hidden neural activation, or background process becomes behavioral evidence only relative to a declared observational level and attribution rule. Otherwise every physical change inside a system would count, eliminating useful boundaries. ## 4.2 Behavior and action Behavior is the broader evidential category. Action adds an attribution of agency, organization, control, or purposive relevance. A reflex, drift, involuntary movement, policy output, and failed attempt can be behavioral without satisfying a demanding theory of action. Conversely, an omission may qualify as action when an agent could and was expected to intervene, even though no overt movement occurred. Action is therefore not reducible to a visible event. The framework treats action attribution as typed and defeasible. Researchers must specify whether an event is merely attributed to a system, controlled by it, selected by a policy, intended, reason-guided, or normatively accountable. ## 4.3 Behavior and interaction Behavior can be attributed to one system relative to an environment. Interaction requires reciprocal constraint between distinguishable systems. An agent\'s behavior may occur within an interaction, but not every behavior is interactive, and an interaction trace contains events attributable to multiple participants and mediating structures. Behavior is therefore a component and perspective on interaction, not its synonym. ## 4.4 Behavior and performance Performance evaluates behavior against a task, norm, utility, or success criterion. The same behavioral trajectory can be high-performing under one objective and poor under another. Completion, reward, speed, accuracy, and efficiency are evaluative functions over behavior; they are not behavior itself. ## 4.5 Behavior and latent explanation Intention, belief, preference, confidence, strategy, habit, expertise, attention, workload, and policy are not directly observed in ordinary traces. They are latent or theoretical variables inferred from behavior, reports, interventions, and auxiliary measurements. A scientific representation must preserve this evidential asymmetry. An action log can constrain interpretations but rarely identifies one uniquely. # 5. Canonical Definition Behavior is a bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributable to a system in relation to its environment under a declared observation model. Each clause is necessary for scientific use: Bounded: the behaving system and relevant environment must be specified.\ Temporally extended: behavior is identified through ordering, duration, transition, recurrence, or maintained regulation.\ Observable or recoverable: evidence must be accessible through declared instruments or records.\ Attributable: the trajectory must be assigned to a system by an explicit causal, control, ownership, or analytic rule.\ Relational: behavior is interpreted relative to environmental conditions and opportunities.\ Observation-model relative: event types, granularity, and uncertainty depend on how the phenomenon is measured. This definition does not require consciousness, intention, semantic understanding, optimality, success, movement, or direct observation by a human. It also does not claim that behavior exists only when observed. Rather, scientific claims about behavior require an observation model connecting the target process to evidence. # 6. Behavioral Event and Segmentation A behavioral event is not a self-identifying atom. It is a temporally bounded segment of a trace classified under an event type and attributed to a system. Segmentation may be physical, functional, task-relative, protocol-defined, or statistically inferred. Different segmentations can be valid for different explanatory questions. The smallest useful unit is therefore not universally a click, movement, command, or state transition. It is the minimal discriminable segment required by a declared explanatory and measurement contract. For motor control this may be a subsecond trajectory; for HCI it may be an operation; for organizational activity it may be a coordinated episode; for reinforcement learning it may be a time step; for discourse it may be a turn or act. Units must not be compared across studies without declaring their segmentation rules. ----------------------------------------------------------------------- **Level** **Examples** **Evidential status** ----------------------- ----------------------- ----------------------- Record Sensor sample, log Directly produced by an line, video frame, instrument; not yet a timestamp behavioral claim. Detected event Threshold crossing, Derived from records by message receipt, button an explicit detector. activation Attributed behavioral Agent selected command; Detected event assigned event robot avoided obstacle to a system and behavioral type. Episode Search sequence; repair Temporally grouped attempt; conversation events under boundary turn cluster and completion rules. Pattern Habitual route; Regularity across oscillation; repeated events or episodes. error Action Intentional, Requires additional policy-selected, agency criteria. controlled, or normatively attributable event Strategy Higher-order Latent or model-based; organization across not directly read from actions and the trace. contingencies Outcome/performance Success, reward, error, Evaluation over traces, cost, completion not behavior itself. ----------------------------------------------------------------------- # 7. Behavior Ontology ----------------------------------------------------------------------- **Entity** **Definition** **Examples** ----------------------- ----------------------- ----------------------- System Entity or analytically Human, animal, robot, bounded organization to software agent, group. which behavior is attributed. Environment Conditions and entities Physical setting, outside the selected interface, other system boundary agents, institutional relevant to the rules. behavior. State Declared description of Position, screen state, system or environment belief state, at a time or interval. physiological state. Observation model Mapping from target Logging schema, coding processes to records protocol, sensors. and event categories. Record Instrument-produced Event log, video frame, datum with provenance telemetry. and timestamp. Event Segment classified Command invocation, under explicit gaze transition. detection rules. Attribution Rule connecting an Control ownership, event or persistence to causal intervention, a system. authorship. Behavioral episode Bounded sequence or Search, repair, concurrent structure of negotiation. attributed events. Context Conditions needed to Task, opportunities, interpret or compare policy, history, behavior. projection. Trace Time-indexed, partially Session trace, ordered collection of multi-agent protocol records and derived trace. events. Outcome State or evaluation Completion, failure, following a trace or reward, harm. episode. Latent construct Unobserved variable Belief, intention, proposed to explain strategy, workload. distributions of evidence. Uncertainty Limits on detection, Confidence intervals, timing, attribution, missing data, competing state, or codings. interpretation. ----------------------------------------------------------------------- # 8. Behavioral Grammar A behavioral grammar specifies admissible composition without claiming that behavior is linguistic. The minimum grammar distinguishes records, events, episodes, and explanatory annotations. Record r ::= \\ Event e ::= detect(type, interval, records, rule)\ Attributed event b ::= attribute(system, event, relation, confidence)\ Episode q ::= compose(boundary, order, {b}, context, completion)\ Trace τ ::= partial-order({records, events, episodes}, clocks, missingness)\ Interpretation i ::= infer(construct, evidence-set, model, alternatives, uncertainty)\ Outcome o ::= evaluate(trace-or-episode, criterion, tolerance) Composition operators include sequential composition (;), concurrency (\|\|), choice (+), iteration (\*), interruption (!), omission (Ø under an expectation model), and nesting (\[ \]). These operators describe trace organization. They do not imply purpose or meaning by themselves. # 9. Trace Model A scientific trace should be modeled as more than an ordered list. Distributed and asynchronous systems require partial ordering, multiple clocks, uncertain timestamps, concurrent events, hidden state, and provenance. Let a behavioral trace be: τ = \ R is the set of raw records. E is the set of detected events. A maps events to attributed systems and relation types. Q is a set of episodes or higher-order segmentations. ≺ is a temporal or causal partial order. C is context, including task, opportunity profile, projection, permissions, environment, and prior history. Ω records uncertainty, missingness, detector error, attribution confidence, and competing annotations. A trace is evidence, not a complete account of behavior. What was not instrumented may be absent. Identical traces may arise from different mechanisms; different traces may instantiate the same strategy or task outcome. Trace equivalence must therefore be typed by observables, granularity, context, and tolerance. # 10. Evidence Hierarchy -------------------------------------------------------------------------- **Level** **Claim type** **Example** **Primary risk** ----------------- ----------------- ----------------- -------------------- 1\. Physical or Instrument output Timestamped log, Calibration error, digital record with provenance video, sensor missingness, clock sample drift. 2\. Derived Deterministic or Duration, path Algorithm and observable statistical length, threshold feature from transition count dependence. records 3\. Detected Segment under Click, utterance Segmentation and event declared rule boundary, classifier error. collision 4\. Behavioral Event assigned to User issued Shared control, attribution a system command automation, accidental activation. 5\. Episode or Composition Search episode, Boundary choice and pattern across events repeated checking multiple valid decompositions. 6\. Functional Role relative to Error correction, Same trace may serve interpretation task or exploration different functions. regulation 7\. Latent Unobserved Belief, Underdetermination construct explanatory intention, and model inference variable strategy, dependence. preference 8\. Causal Mechanism claimed Feedback control, Confounding, reverse explanation to generate learning, habit causation, omitted behavior variables. -------------------------------------------------------------------------- # 11. Behavior Taxonomy ----------------------------------------------------------------------- **Axis** **Types** **Question answered** ----------------------- ----------------------- ----------------------- Attribution System-generated; Who or what generated environmentally the trajectory? imposed; jointly produced; uncertain Control Controlled; automatic; What control relation reflexive; stochastic; is supported? externally driven Temporal form Event; persistence; How is behavior sequence; cycle; organized in time? concurrent coordination; developmental change Environmental relation Reactive; anticipatory; How does it relate to regulatory; environmental exploratory; conditions? communicative; transformative Learning status Novel; learned; What history is habitual; adapted; evidenced? transferred; innate/developmental Social organization Individual; dyadic; Where is behavioral collective; organization located? distributed; institutional Outcome status Attempted; interrupted; What occurred relative failed; successful; to a criterion? compensatory; reversible Observability Directly recorded; What evidence supports indirectly recovered; the claim? inferred; unobserved ----------------------------------------------------------------------- # 12. Cross-System Comparative Cases Human-computer command. A user invokes a command, the system logs an event, and a state transition follows. The record supports that an input occurred and may support attribution to the account or device. It does not alone establish intention, understanding, confidence, or authorship by the human rather than automation. Animal navigation. A trajectory through an environment is directly behavioral under an organism boundary. Explaining it as foraging, homing, or exploration requires environmental and functional evidence. Tinbergen\'s distinctions show that mechanism, development, adaptive function, and phylogeny answer different questions about the same behavior. Robot obstacle avoidance. Sensor, control, and motion traces support a mechanistic account. Goal-directedness can be specified functionally without assuming consciousness. The behavior may be generated by feedback control, a learned policy, or a fixed rule; output similarity does not identify the mechanism. Reinforcement-learning agent. A state-action-reward trajectory is behavior under the model, while the policy is a generative disposition over actions. The environment\'s state representation is analytical, not necessarily the system\'s own representation. Reward is an evaluative signal, not evidence of subjective desire. Distributed team activity. The relevant behavior may not be attributable to any individual. Coordination emerges across people, artifacts, and representations. A group-level episode requires explicit composition and boundary rules, preserving individual and collective levels rather than replacing one with the other. Conversational system. Generated text is observable output. Treating it as assertion, promise, refusal, deception, or understanding requires semantic, institutional, and agency criteria. Surface linguistic form is insufficient to establish the latent construct. # 13. Recurring Behavioral Structures - Feedback loops: outputs alter conditions that shape later behavior. - Selection under constraints: behavior is chosen or generated from an opportunity structure, whether explicitly represented or not. - Temporal hierarchy: events compose into episodes, routines, strategies, and developmental trajectories. - Partial observability: the behaving system and observer have incomplete and different access to state. - Adaptation: response distributions change with history, consequences, training, and environmental structure. - Equifinality and multifinality: different mechanisms can produce similar traces, and similar initial traces can lead to different outcomes. - Context sensitivity: task, environment, social rules, projection, and prior activity alter the meaning of identical events. - Coordination: behavior may be jointly organized across agents and artifacts. - Error and recovery: failed or interrupted action changes subsequent behavior and opportunity. - Persistence and omission: maintaining a state or not acting can be behavior under control or expectation models. # 14. Latent Variables Latent variables are legitimate when they support testable measurement models, interventions, or predictions. They become scientifically dangerous when labels merely redescribe the behavior they are supposed to explain. Saying that a user clicked because of a preference, inferred only from the click, is circular unless preference independently predicts behavior across conditions. A latent claim should declare: construct definition; indicators; measurement model; temporal ordering; alternative explanations; identification assumptions; expected interventions; uncertainty; and falsifying observations. Self-report is additional behavior and evidence, not transparent access to an internal state. Model-generated hidden states are computational variables, not automatically psychological constructs. The recommended policy is typed inference. Terms such as intended, believed, understood, attended, preferred, confused, and strategic must be explicitly marked as reported, experimentally manipulated, model-inferred, or theoretically attributed. # 15. Behavioral Evidence Contract ----------------------------------------------------------------------- **Field** **Required declaration** ----------------------------------- ----------------------------------- Target system Boundary, level, and ownership criteria. Environment Relevant external entities, conditions, institutions, and other agents. Observation model Sensors, logs, coding scheme, channels, sampling, and calibration. Temporal model Clock, ordering, latency, synchronization, interval conventions. Event vocabulary Types, detection rules, segmentation, and granularity. Attribution rule Why an event is assigned to a system and with what confidence. Context Task, projection, opportunity profile, permission, history, and incentives. Outcome criteria Success, failure, cost, reward, safety, or completion definitions. Latent constructs Measurement model, indicators, alternatives, and identification assumptions. Uncertainty Missing data, detector error, attribution ambiguity, and confidence. Comparison scope Populations, systems, settings, invariants, metrics, and tolerances. Failure conditions Conditions under which the trace cannot support the intended claim. ----------------------------------------------------------------------- # 16. Falsification and Rival Accounts -------------------------------------------------------------------------- **Claim tested** **Falsifying or **Consequence** contrary evidence** ----------------------- ----------------------- -------------------------- Behavior can be defined Omissions, controlled Retain broader trajectory as observable movement persistence, messages, definition. alone. and software outputs are systematically excluded. Behavior is simply Transitions occur Keep behavior as state transition. without useful attributed trace over attribution; a single transitions. transition omits temporal organization and environment relation. Behavior is action. Reflexes, failures, Keep action as typed involuntary outputs, subset or interpretation. and non-agentive systems remain scientifically relevant. Policy is behavior. Different realized Separate generative traces arise from one disposition from policy and the same realization. trace from different policies. Logs directly reveal Instrument changes, Preserve behavior. automation, shared record-event-attribution control, and missing hierarchy. channels alter recorded events. Latent states can be Multiple latent models Require identified read from traces. fit the same measurement and causal observations or fail models. under intervention. A universal atomic unit Valid units vary by Use contract-relative exists. explanatory level and minimal units. measurement resolution. Existing theories are Cross-system comparison Retain shared typed trace fully sufficient repeatedly conflates framework only if it without synthesis. records, actions, improves reliability and states, and latent prediction. constructs. -------------------------------------------------------------------------- # 17. Threats to Validity The proposed definition is intentionally scientific rather than exhaustive of ordinary language. It may classify phenomena differently from legal, moral, clinical, or folk-psychological accounts. The term attributable risks importing causal assumptions into description; this is mitigated by requiring attribution types and uncertainty. The framework may privilege traceable computational cases. Human and animal behavior can involve embodied, affective, social, historical, and institutional structures not recoverable from event logs. Distributed cognition also makes system boundaries contested rather than simply discoverable. Formal traces can encourage false completeness. Missing channels, observer effects, coding choices, and asynchronous processes may materially alter conclusions. Behavioral categories can become reified, particularly when inferred properties are attached to demographic groups. Culture, language, occupation, disability, and experience should enter through measured contexts and mechanisms rather than deterministic labels. Finally, the framework\'s value is unproven until independent researchers can annotate common datasets more consistently, compare behavior across implementations, and improve explanatory or predictive performance without laundering interpretation as observation. # 18. Implications for Computational Interaction Research The framework places behavior after interaction and opportunity but before measurement and prediction. Interaction specifies reciprocal coupling. Opportunity specifies typed action availability. Behavior records the realized, attributed trajectory. Measurement establishes how traces and constructs are operationalized. Explanation connects behavior to mechanisms without assuming that representation directly causes action. A complete analysis should therefore distinguish: what the system made possible; what was exposed or believed; what records were produced; which events were detected; which events were attributed as behavior; which actions or strategies were inferred; and which outcomes were evaluated. This separation prevents common errors such as treating an unselected control as unnoticed, a pause as confusion, task completion as understanding, or equal outcomes as equal behavior. The model also makes later similarity research tractable. Two interactions may be semantically equivalent while producing different behavioral traces; two traces may be structurally different while instantiating the same policy; and behavior may be observationally equivalent under one instrument but distinguishable under another. # 19. Conclusion Existing behavioral theories are sufficient for their established domains but do not provide a single evidence-preserving vocabulary for computational interaction. The missing contribution is not a new substance called computational behavior. It is a disciplined synthesis separating records, events, attribution, episodes, action, performance, and latent explanation. Behavior should be represented as a bounded, temporally extended, observation-model-relative trajectory attributable to a system in relation to its environment. This account supports humans, animals, robots, software agents, and distributed systems without requiring intention or reducing behavior to arbitrary state change. It preserves the distinction between what occurred and why it occurred. The paper\'s principal conclusion is therefore: existing theories are conceptually sufficient but require a shared typed trace and evidence framework for computational interaction research. The framework should be retained only if it improves annotation reliability, cross-system comparison, causal clarity, and out-of-sample explanation or prediction. # 20. Reusable Artifacts ## 20.1 Canonical vocabulary ----------------------------------------------------------------------- **Term** **Definition** ----------------------------------- ----------------------------------- Behavior A bounded, temporally extended trajectory of observable or recoverable changes, outputs, or regulated persistence attributable to a system in relation to its environment under a declared observation model. Behavioral event A temporally bounded segment of a trace classified under an event type and attributed to a system. Action Behavior attributed as controlled, selected, intentional, reason-guided, or normatively attributable under a declared theory of agency. State A declared description of a system or environment at a time or interval. Trace A time-indexed or partially ordered collection of records, detected events, attributions, episodes, context, and uncertainty. Episode A bounded composition of behavioral events under explicit initiation, continuation, and completion rules. Pattern A regularity across events or episodes under a declared similarity rule. Performance Evaluation of behavior relative to a task, criterion, utility, norm, or tolerance. Latent construct An unobserved variable proposed to explain or predict evidence through a measurement or causal model. Behavioral evidence Records and derived claims whose provenance, transformation, attribution, and uncertainty are declared. ----------------------------------------------------------------------- ## 20.2 Minimal annotation schema \ ## 20.3 Behavioral comparison protocol - Declare systems, environments, levels, and boundaries. - Align observation channels and verify instrumentation equivalence. - Normalize clocks, sampling, missingness, and event-detection rules. - Compare raw records before comparing attributed event labels. - Declare segmentation granularity and episode boundary rules. - Separate descriptive trace metrics from task-performance metrics. - Compare latent constructs only through equivalent measurement models. - Control opportunity, projection, task, permission, and prior experience. - Use typed equivalence claims with metrics and tolerances. - Report alternative annotations and uncertainty. # 21. References Beer, R. D. (1995). A dynamical systems perspective on agent-environment interaction. Artificial Intelligence, 72, 173-215. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Lawrence Erlbaum. Davidson, D. (1980). Essays on Actions and Events. Oxford University Press. Dewey, J. (1896). The reflex arc concept in psychology. Psychological Review, 3, 357-370. Engestrom, Y. (1987). Learning by Expanding. Orienta-Konsultit. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263-291. Newell, A., Shaw, J. C., & Simon, H. A. (1958). Elements of a theory of human problem solving. Psychological Review, 65, 151-166. Norman, D. A. (1986). Cognitive engineering. In User Centered System Design. Lawrence Erlbaum. Preece, J., Rogers, Y., & Sharp, H. (2015). Interaction Design: Beyond Human-Computer Interaction. Wiley. Reason, J. (1990). Human Error. Cambridge University Press. Rosenblueth, A., Wiener, N., & Bigelow, J. (1943). Behavior, purpose and teleology. Philosophy of Science, 10, 18-24. Ryle, G. (1949). The Concept of Mind. Hutchinson. Skinner, B. F. (1938). The Behavior of Organisms. Appleton-Century. Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. Tinbergen, N. (1963). On aims and methods of ethology. Zeitschrift fur Tierpsychologie, 20, 410-433. von Wright, G. H. (1971). Explanation and Understanding. Cornell University Press. Wiener, N. (1948). Cybernetics. MIT Press. ======================================================================== ## FILE: docs/02_Research_Papers/09_Measurement/Measurement_Toward_a_Scientific_Framework_for_Interaction_Research.md (846 lines, 35.3 KiB) ======================================================================== **Measurement** *Toward a Scientific Framework for Interaction Research* Foundational research paper # Abstract Computational interaction research measures events, traces, task outcomes, subjective reports, system states, and inferred constructs such as discoverability, confidence, workload, belief, strategy, and opportunity. These are often treated as if they belonged to a single evidential category. They do not. Measurement theory distinguishes an empirical relational structure from its numerical representation; psychometrics distinguishes observed responses from latent constructs and requires validity evidence for score interpretation; metrology requires an explicit measurand and uncertainty statement; experimental psychology distinguishes manipulation, observation, and inference; HCI evaluation makes performance context-dependent; and systems engineering emphasizes traceability from requirements to evidence. This paper concludes that existing measurement theories are sufficient in principle, but computational interaction research requires a shared measurement architecture that integrates them. The proposed architecture defines a measurement claim as a contract among a declared construct, unit and level of analysis, observation model, instrument, coding or transformation rule, numerical scale, uncertainty model, validity argument, and admissible interpretation. It separates direct observations, derived variables, model-based estimates, and latent inferences; forbids interpreting logging precision as construct validity; and requires comparison claims to declare invariance, context, population, task, projection, and tolerance conditions. The paper supplies a measurement ontology, canonical metrics, evidence taxonomy, experimental framework, construct cards, uncertainty budgets, comparability tests, and falsification criteria. # 1. Problem Statement Interaction research routinely reports time, success, error, clicks, paths, ratings, physiological signals, and model predictions. The apparent precision of these quantities can obscure a prior question: what exactly has been measured? A timestamp is directly recorded; hesitation is inferred. A control was displayed; discoverability was not thereby measured. An action was executed; intention, understanding, confidence, or strategy were not directly observed. A task was completed; equal access, equal opportunity, and equivalent interaction were not established. The central problem is therefore not a shortage of metrics. It is the absence of a common framework that connects theoretical constructs to observations without collapsing observation, transformation, inference, and interpretation. Computational interaction research requires a measurement theory that is implementation-independent, explicit about uncertainty, and compatible with system variables, behavioral traces, subjective reports, and latent constructs. # 2. Literature Review Method The review used a concept-centered synthesis across measurement theory, psychometrics, metrology, statistics, experimental psychology, HCI evaluation, human factors, information theory, and systems engineering. Foundational and primary sources were prioritized: representational measurement theory for numerical representation and scale admissibility; Cronbach and Meehl for construct validity; Messick for validity as an argument about score meaning and use; the Guide to the Expression of Uncertainty in Measurement and NIST guidance for measurands and uncertainty; ISO 9241-11 for context-dependent usability; classical reliability and generalizability theory; signal detection theory; causal inference; and established HCI measures. The synthesis was constrained by four tests. First, no new construct was retained when an established measurement concept already sufficed. Second, every proposed measurement category had to support operationalization and falsification. Third, direct observations were separated from derived and latent quantities. Fourth, comparison claims were required to state the transformations and scope under which scores remain interpretable. # 3. What Measurement Is Measurement is not merely assigning a number. In representational measurement theory, numerical assignments are justified when the numerical structure preserves relevant relations in an empirical structure, and the permissible transformations of the scale determine which comparisons and statistics remain meaningful. This yields two central requirements: representation and uniqueness. A measure must preserve declared empirical relations, and its interpretation must respect the scale transformations under which that representation remains valid. Metrology adds the measurand: the quantity intended to be measured. A result is incomplete without specification of the measurand, method, conditions, and uncertainty. Psychometrics adds a further constraint: many interaction constructs are not directly observable. Scores are evidence-bearing observations whose interpretation as measures of a construct requires a nomological and empirical argument. For computational interaction, measurement is therefore defined as: A rule-governed process that maps observations of a declared interaction phenomenon into a representational structure, together with an uncertainty statement and a validity argument specifying which interpretations and comparisons are warranted. This definition distinguishes measurement from logging, counting, classification, estimation, and explanation. Logs may supply observations. Counts may summarize observations. Classifiers may derive labels. Models may estimate latent variables. None of these alone establishes that the resulting value measures the intended construct. # 4. Measurement Ontology The minimum ontology contains the following entities and relations. Construct: a theoretical property, relation, process, or outcome to be investigated.\ Measurand: the specific quantity or attribute intended to be measured in a declared case.\ Unit of analysis: the entity or aggregate to which the measurement is attributed, such as event, action, episode, participant, dyad, system, task, session, or population.\ Level of analysis: the temporal, organizational, representational, or social level at which the claim is made.\ Observation: a recorded state, event, signal, report, or trace element obtained through a declared observation process.\ Instrument: the mechanism that produces or records observations, including logger, sensor, questionnaire, protocol, annotator, or system model.\ Operationalization: the rule connecting a construct to observable indicators and transformations.\ Indicator: an observable or derived variable used as evidence about a construct.\ Score: a numerical or categorical representation produced by the measurement procedure.\ Scale: the mathematical structure and permissible transformations governing the score.\ Estimator: a procedure that infers an unknown quantity from observations.\ Uncertainty: quantified incompleteness of knowledge about the measurand or score interpretation.\ Validity argument: the evidence and reasoning supporting an intended interpretation and use.\ Reliability: consistency of scores under declared replications, not truth or validity.\ Comparison scope: the population, task, context, projection, and tolerance under which scores may be compared.\ Decision rule: a threshold or mapping from measurements to classifications or actions.\ Evidence record: a traceable package containing observations, transformations, assumptions, and uncertainty. The core relation is not construct -\> metric. It is: Construct -\> operationalization -\> observation process -\> observations -\> transformation or estimator -\> score -\> interpretation. Validity and uncertainty apply across this chain, not only to the final score. # 5. Observable, Derived, and Latent Variables Interaction measurements should be classified by epistemic status. Directly recorded variables are produced by a declared instrument with minimal semantic transformation: timestamps, event identifiers, system states, command invocations, pointer coordinates, sensor values, text responses, and explicit ratings. They remain instrument- and boundary-dependent. Coded observations apply a rule to raw records: error type, action category, recovery event, strategy segment, or successful transition. Coding introduces a model and may require inter-rater or algorithmic reliability. Derived variables are deterministic or explicitly statistical transformations of observations: duration, path length, transition count, error rate, entropy, precision, recall, edit distance, or proportion successful. Derivation does not by itself validate the construct interpretation. Model-based estimates are quantities inferred under a probabilistic or computational model: latent state, posterior belief, workload estimate, policy parameter, hazard, random effect, or predicted success probability. Their meaning depends on model assumptions, identifiability, calibration, and fit. Latent constructs are theoretical variables not directly observed: confidence, understanding, intention, trust, discoverability, cognitive workload, strategy, perceived opportunity, or expertise. They require multiple indicators, experimental interventions, convergent and discriminant evidence, or a validated measurement model. A single behavioral event cannot ordinarily identify a latent construct. Interpretive conclusions are claims about mechanisms or causes. They are not measurements, even when based on measured variables. # 6. Construct Validity Construct validity is the central problem for interaction measurement because many target constructs are indirect. Cronbach and Meehl require a network of theoretical relations connecting the construct to observations and other constructs. Messick further treats validity as an integrated argument about score meaning and use, rather than a property possessed by an instrument in isolation. A defensible interaction measurement should address: Content relevance: indicators sample the intended construct rather than a convenient proxy.\ Structural validity: the scoring or latent-variable structure matches the proposed construct structure.\ Convergent evidence: different methods intended to measure the same construct show the expected relationship.\ Discriminant evidence: the measure is separable from adjacent constructs.\ Criterion relations: scores relate to external outcomes as theory predicts.\ Known-groups or intervention evidence: manipulations expected to change the construct change the score, while controls do not.\ Process evidence: the observation-generating process matches the proposed interpretation.\ Generalization: score meaning remains stable across relevant populations, tasks, contexts, and projections.\ Consequential validity: intended uses and foreseeable misuses are evaluated where scores guide decisions. No single correlation establishes validity. Validation is cumulative and claim-specific. A measure may be valid for comparing discovery time within one task yet invalid for ranking general interface quality. # 7. Reliability, Reproducibility, and Generalizability Reliability concerns consistency under repeated measurement conditions. It may include temporal stability, internal consistency, inter-rater agreement, inter-instrument agreement, or repeated-trial consistency. High reliability is necessary for many comparisons but is not sufficient for validity; a logger can record the wrong event with perfect consistency. Reproducibility requires sufficient specification for independent researchers to implement the measurement process and obtain results consistent within declared uncertainty. Computational interaction studies should preserve event schemas, clocks, task definitions, exclusions, preprocessing, coding manuals, estimator specifications, software versions, and analysis decisions. Generalizability concerns variation across persons, tasks, items, systems, contexts, and occasions. A score is not automatically an attribute of a person or interface. Many HCI measures are relational properties of users, goals, systems, and contexts. Generalizability theory and multilevel models are therefore more appropriate than treating all variance outside the focal factor as undifferentiated error. A measurement report should state the intended universe of generalization and identify which facets were sampled, fixed, randomized, or omitted. # 8. Uncertainty Uncertainty in interaction research has several sources. Instrument uncertainty includes clock resolution, event loss, sensor error, sampling jitter, synchronization drift, and annotation interface constraints. Operational uncertainty arises from ambiguous event boundaries, task completion rules, segmentation, and competing operational definitions. Sampling uncertainty concerns persons, tasks, items, sessions, and contexts. Model uncertainty concerns functional form, priors, unobserved confounding, missing data, identifiability, and estimator choice. Construct uncertainty concerns whether the indicators support the intended latent interpretation. Context uncertainty concerns whether measurements transfer across projections, devices, languages, cultures, expertise levels, and environments. Decision uncertainty concerns thresholds and the consequences of false classifications. An uncertainty budget should list each source, its treatment, and whether it is quantified, bounded, sensitivity-tested, or unresolved. Confidence intervals alone do not cover model, construct, or scope uncertainty. # 9. Canonical Metric Families No universal scalar interaction metric is supported. The literature instead supports typed metric families. Temporal metrics: latency, duration, inter-event interval, dwell, recovery time, learning rate, and time-to-discovery. Outcome metrics: task success, transition success, goal attainment, partial completion, quality, safety, and persistence of effects. Error metrics: error count, error probability, severity, detectability, correction rate, escalation, and residual harm. Path and sequence metrics: action count, path length, edit distance, state coverage, branching, backtracking, sequence entropy, and conformance to a declared model. Opportunity metrics: precision and recall of believed actions against executable actions, discovery probability, exposure coverage, signaling calibration, reachable-outcome coverage, and recovery visibility. Information metrics: entropy, mutual information, uncertainty reduction, channel capacity, and coding cost, only when the random variables and probabilistic assumptions are defined. Shannon information does not measure meaning, understanding, or usefulness by itself. Resource metrics: physical effort, attentional demand, memory demand, computational cost, energy, bandwidth, and coordination load. Subjective measures: perceived workload, confidence, trust, satisfaction, risk, usability, and perceived reversibility. These are reports under a measurement model, not transparent readings of internal state. Comparative metrics: effect size, equivalence bounds, calibration difference, distributional distance, and invariance tests. Each metric must be tied to a construct card. Metrics should not be combined into an index unless the aggregation rule and trade-offs are theoretically justified. # 10. Measurement Contracts Every reported interaction measure should be accompanied by a measurement contract containing: 1\. Construct and intended interpretation.\ 2. Measurand and unit of analysis.\ 3. Scope conditions: population, task, system, projection, context, and time.\ 4. Observation model and instrument.\ 5. Event, state, and boundary definitions.\ 6. Operationalization and indicators.\ 7. Transformation, coding, or estimator.\ 8. Scale type and permissible operations.\ 9. Missingness, exclusions, and preprocessing.\ 10. Reliability evidence.\ 11. Validity evidence.\ 12. Uncertainty budget.\ 13. Comparison and invariance assumptions.\ 14. Failure conditions and prohibited interpretations.\ 15. Reproducibility artifacts. This contract is the minimum reusable unit of measurement specification. It makes the evidential chain inspectable and supports later interaction-similarity and comparative-interaction research. # 11. Comparability and Measurement Invariance Two scores are comparable only when they preserve an intended interpretation across the cases being compared. Numerical equality is insufficient. The same completion time can arise from different task boundaries, clocks, path constraints, or strategies. The same questionnaire total can have different factor structures or response meanings across populations. Comparability requires at least: Construct identity: the same construct interpretation is intended.\ Operational correspondence: indicators and coding rules have equivalent roles.\ Scale compatibility: permissible transformations and units are aligned.\ Measurement invariance: item or indicator relations remain stable where latent scores are compared.\ Context declaration: task, goals, authority, projection, and environment are controlled or modeled.\ Sampling alignment: populations and units are comparable or adjusted.\ Uncertainty compatibility: uncertainty is reported on commensurate terms.\ Tolerance: equivalence is defined by a prespecified practically meaningful bound. When these conditions fail, the correct result is typed non-comparability, not forced normalization. # 12. Experimental Framework The recommended experimental framework separates construct, intervention, measurement, and inference. Phase 1 - Theory and construct specification. Define the construct, competing explanations, unit and level of analysis, and causal role. Phase 2 - Measurement design. Create construct cards, select indicators, define events and boundaries, specify instruments, and preregister uncertainty and exclusion rules. Phase 3 - Manipulation and comparison design. Specify treatment, control, manipulation checks, nuisance variables, and minimum meaningful effects or equivalence bounds. Phase 4 - Data generation. Record raw observations with provenance, synchronized clocks, immutable event identifiers, and declared missingness. Phase 5 - Transformation and coding. Apply versioned rules; preserve raw-to-derived traceability; assess rater or algorithmic agreement. Phase 6 - Estimation. Fit models appropriate to nesting, repeated measures, censoring, measurement error, and uncertainty. Avoid treating participant or task variance as independent observations. Phase 7 - Validation. Test convergent, discriminant, structural, intervention, criterion, and generalization evidence. Phase 8 - Sensitivity and falsification. Test alternative operationalizations, priors, exclusions, model forms, and rival mechanisms. Phase 9 - Reporting. Publish the measurement contract, uncertainty budget, analysis specification, and prohibited interpretations. # 13. Evidence Taxonomy Evidence should be reported by level. Level 0 - Raw record: minimally processed event, signal, state, or report.\ Level 1 - Verified observation: record checked for provenance, integrity, timing, and instrument behavior.\ Level 2 - Coded observation: category assigned under a documented rule.\ Level 3 - Derived measure: deterministic or statistical summary of observations.\ Level 4 - Model estimate: parameter, posterior, or latent score inferred under a declared model.\ Level 5 - Construct evidence: multiple measures support an interpretation of a theoretical construct.\ Level 6 - Mechanism evidence: interventions, temporal ordering, and rival tests support a generating process.\ Level 7 - Generalized claim: evidence supports transfer across declared populations, tasks, systems, or projections. Higher levels depend on lower levels but do not become direct observations. A mechanism claim should remain labeled as inference even when strongly supported. # 14. Falsification Tests The framework should be narrowed or rejected if the following occur. Measurement redundancy: established measurement theory can already express every requirement without any interaction-specific coordination artifact. In that case only a domain checklist, not a new framework, is warranted. Non-operational constructs: central interaction constructs cannot be connected to observable indicators with discriminant validity. No incremental validity: specialized opportunity, projection, or interaction metrics fail to explain or predict outcomes beyond ordinary task, system, and participant variables. Invariance failure: measures change interpretation across projections, populations, or tasks despite apparent numerical comparability. Observer dependence without calibration: event boundaries and coding cannot achieve reproducible agreement. Uncertainty dominance: measurement and model uncertainty exceed the effects under investigation. Causal ambiguity: proposed mechanisms remain indistinguishable from simpler rival explanations under intervention. Metric instability: conclusions reverse under equally defensible operationalizations or preprocessing choices. The framework survives only if it improves traceability, construct validity, and comparative inference relative to untyped metric reporting. # 15. Threats to Validity The synthesis risks over-formalizing phenomena that are situated, socially negotiated, or emergent. Not every meaningful interaction property is naturally scalar. Qualitative observations may provide stronger construct evidence than forced quantification. Measurement contracts can create procedural compliance without genuine validity. Explicit fields do not substitute for theory or empirical validation. The framework inherits disputes within measurement theory, including whether all measurement requires numerical structural representation and how causal accounts of measurement relate to representational accounts. HCI constructs often depend on context of use. Generalization across tasks, cultures, languages, accessibility conditions, and expertise may be limited. Measurement invariance may fail for theoretically meaningful reasons rather than instrument defects. Instrumentation can change the phenomenon being measured through reactivity, latency, logging overhead, surveillance effects, or task restructuring. Finally, evidence quality is not reducible to a linear hierarchy. Different questions require different forms of evidence; the taxonomy records dependency and inferential distance, not universal superiority. # 16. Implications for Interaction Research The measurement framework completes the transition from conceptual ontology to empirical research. Prior work distinguishes ontology, semantics, representation, interpretation, opportunity, interaction, and behavior. Measurement adds the rules by which claims about these constructs can be connected to evidence without collapsing them. For representation research, it requires typed equivalence tests and invariance conditions. For opportunity research, it separates executable, exposed, signaled, believed, selected, and successful actions into different measurands. For behavior research, it converts traces into evidence through declared segmentation and coding. For interaction comparison, it supplies equivalence bounds and comparability tests. For prediction, it separates measurement quality from model performance. The central implication is that computational interaction research should stop treating metric labels as self-interpreting. Time, error, success, workload, trust, discoverability, and usability are valid only through explicit measurement contracts. # 17. Conclusion Existing measurement theory, psychometrics, metrology, statistics, experimental psychology, HCI evaluation, and systems engineering are sufficient to explain how interaction phenomena can be measured. No new foundational theory of measurement is required. A domain-specific synthesis is nevertheless necessary because interaction research combines system events, behavioral traces, subjective reports, relational constructs, and latent interpretations in ways that invite category errors. The warranted contribution is a shared measurement architecture, not a new measurement primitive. The primary conclusion is: Interaction phenomena should be measured through explicit contracts linking constructs to observation processes, transformations, uncertainty, validity evidence, and comparison scope. Observations, derived metrics, latent estimates, and explanatory conclusions must remain typed and traceable throughout the evidential chain. # 18. Reusable Artifacts ## A. Measurement Ontology ----------------------------------------------------------------------- Entity Definition Role ----------------------- ----------------------- ----------------------- Construct The theoretical Theory property, relation, process, or outcome under investigation. Measurand The specific quantity Specification intended to be measured in a declared case. Observation Recorded event, state, Empirical signal, or report. Instrument Mechanism producing or Method recording observations. Indicator Observable or derived Operationalization evidence linked to a construct. Score Representational output Representation of a measurement procedure. Estimator Rule for inferring an Model unknown quantity from observations. Uncertainty Incomplete knowledge Epistemic about measurand or interpretation. Validity argument Evidence supporting an Inference intended score interpretation and use. Comparison scope Conditions under which Boundary values may be compared. ----------------------------------------------------------------------- ## B. Canonical Metric Registry ----------------------------------------------------------------------------- Construct family Candidate metrics Required controls Prohibited inference ----------------- -------------------- -------------------- ----------------- Discovery Unaided discovery Exposure/signaling Visibility alone probability; held or modeled; is not discovery time-to-discovery; prior knowledge prompt level measured Believed action Precision/recall Judgment elicited Attempts alone do set against executable before feedback; not identify action set; executable set belief confidence independently calibration verified Behavioral path Transition count; Common state/action Shorter is not path cost; entropy; ontology and universally backtracking; segmentation better conformance Recovery Detection time; Error severity and Undo availability repair initiation; actual recovery is not perceived successful recovery; graph declared reversibility residual effect Performance Effectiveness, Users, goals, Task completion efficiency, quality, context, and success is not general safety criteria declared usability Subjective state Rating scale or Response process and Report is latent score with invariance tested evidence, not reliability and transparent validity evidence internal state Representation Equivalence bounds; Semantic target and Informational comparison effect sizes; task held constant equivalence does distributional not imply distance behavioral equivalence ----------------------------------------------------------------------------- ## C. Evidence Taxonomy ------------------------------------------------------------------------------------------ Level Meaning Example Minimum requirement ----------------- --------------------------- ------------------ ------------------------- 0 Raw record Event, signal, state, Logger packet; Provenance and integrity report audio sample 1 Verified Validated record Synchronized event Instrument behavior observation timestamp checked 2 Coded Rule-applied category Error type; action Coding reliability observation class 3 Derived measure Deterministic/statistical Duration; success Derivation traceable summary rate 4 Model estimate Quantity inferred under Latent workload; Fit, identifiability, model hazard calibration 5 Construct Multiple indicators support Discoverability Convergent/discriminant evidence construct evidence validity 6 Mechanism Intervention supports Signaling changes Rival explanations tested evidence process discovery via belief 7 Generalized Claim extends across scope Cross-projection Sampling and invariance claim invariance evidence ------------------------------------------------------------------------------------------ ## D. Construct Card - Construct name and definition - Adjacent constructs and discriminant boundary - Causal or explanatory role - Unit and level of analysis - Candidate indicators - Expected convergent and discriminant relations - Manipulations expected to change the construct - Conditions expected not to change it - Known confounds - Permitted interpretations - Prohibited interpretations - Falsification conditions ## E. Measurement Contract 1. Construct and intended interpretation 2. Measurand 3. Unit and level of analysis 4. Population, task, system, projection, context, and time scope 5. Observation model and instrument 6. Event, state, and boundary definitions 7. Operationalization and indicators 8. Transformation, coding, or estimator 9. Scale type and permissible operations 10. Missingness, exclusions, and preprocessing 11. Reliability evidence 12. Validity evidence 13. Uncertainty budget 14. Comparison and invariance assumptions 15. Failure conditions and prohibited interpretations 16. Reproducibility artifacts ## F. Uncertainty Budget Template ------------------------------------------------------------------------------------------ Source Mechanism Direction/magnitude Treatment Residual risk ----------------------- -------------- --------------------- -------------- -------------- Instrument Clock/synchronization Boundary/segmentation Coding Sampling Missingness Model form Construct interpretation Context transfer Decision threshold ------------------------------------------------------------------------------------------ ## G. Experimental Protocol 1\. Define construct, rival explanations, unit, and level. 2\. Create construct card and measurement contract. 3\. Specify treatment, control, manipulation check, nuisance variables, and equivalence bounds. 4\. Capture raw observations with provenance and synchronized timing. 5\. Apply versioned coding and transformation rules. 6\. Estimate with models appropriate to nesting, censoring, and measurement error. 7\. Validate score interpretation using multiple evidence sources. 8\. Run sensitivity, invariance, and falsification analyses. 9\. Report uncertainty, scope, prohibited interpretations, and reproducibility artifacts. # 19. References Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103(2684), 677-680. Suppes, P., & Zinnes, J. L. (1963). Basic measurement theory. In Handbook of Mathematical Psychology, Vol. 1. Krantz, D. H., Luce, R. D., Suppes, P., & Tversky, A. (1971). Foundations of Measurement, Volume I. Academic Press. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302. Messick, S. (1995). Validity of psychological assessment. American Psychologist, 50(9), 741-749. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105. Lord, F. M., & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. Brennan, R. L. (2001). Generalizability Theory. Springer. JCGM. (2008). Evaluation of measurement data - Guide to the expression of uncertainty in measurement. Taylor, B. N., & Kuyatt, C. E. (1994). Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. ISO 9241-11:2018. Ergonomics of human-system interaction - Part 11: Usability: Definitions and concepts. Macmillan, N. A., & Creelman, C. D. (2005). Detection Theory: A User\'s Guide. Lawrence Erlbaum. Cook, T. D., & Campbell, D. T. (1979). Quasi-Experimentation. Houghton Mifflin. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379-423, 623-656. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Brooke, J. (1996). SUS: A quick and dirty usability scale. In Usability Evaluation in Industry. Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX. In Human Mental Workload. Sauro, J., & Lewis, J. R. (2016). Quantifying the User Experience. Morgan Kaufmann. Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J. (2011). The aligned rank transform for nonparametric factorial analyses. CHI 2011. Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). ======================================================================== ## FILE: docs/02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.md (831 lines, 36.5 KiB) ======================================================================== **Interaction Similarity** *Toward a General Theory of Comparable Interactions* Cross-disciplinary foundational research paper # Abstract Interaction research routinely compares interfaces, traces, users, policies, models, and outcomes using the language of sameness or similarity. The terms are often underspecified. Formal methods show that even behaviorally oriented equivalence divides into trace, testing, simulation, bisimulation, and related relations, each preserving different observations. Psychology and pattern recognition show that similarity depends on selected features, weighting, context, asymmetry, and representation. Process mining shows that model-to-model, log-to-log, and log-to-model comparisons answer different questions. Measurement theory adds a further constraint: numerical comparisons are valid only under declared scales, observation models, uncertainty, and admissible transformations. This paper develops a typed theory of interaction comparison. It concludes that no context-free relation of interaction similarity is scientifically defensible. Interaction token identity is historical identity under a declared boundary; interaction type identity is classification under an explicit abstraction; equivalence is exact preservation relative to a declared observation contract; similarity is graded proximity under specified dimensions and metrics; and incomparability arises when targets, boundaries, observation models, scales, or validity domains cannot be aligned without unsupported assumptions. The paper proposes a layered comparison object spanning semantics, coupling structure, protocol, opportunity, trace, behavior, policy, strategy, outcome, cause, and measurement. It leaves behind a similarity ontology, taxonomy, equivalence hierarchy, similarity contract, comparison protocol, admissible-transformation matrix, and falsification matrix. # 1. Problem Statement Two interactions may share an implementation yet differ because participants, goals, states, permissions, or histories differ. Two different implementations may realize the same protocol or semantic operation. Two traces may be identical while arising from different mechanisms, and different traces may express the same strategy or achieve the same outcome. A novice and an expert can encounter the same projection but possess different believed action sets. Accessibility variants can preserve operation semantics while changing sequence, latency, discoverability, and recovery. The scientific problem is therefore not to ask whether two interactions are simply similar. It is to determine: similar with respect to what object, under which abstraction, for which observer and task, using what evidence, metric, tolerance, and uncertainty model? Without these declarations, similarity claims collapse distinctions established by prior work on representation, opportunity, interaction, behavior, and measurement. # 2. Method The review used a concept-centered comparative method across similarity theory, formal equivalence, graph and sequence comparison, process mining, pattern recognition, behavioral science, machine learning, and HCI. Foundational sources were prioritized: Tversky on feature-based similarity; metric and edit-distance traditions; dynamic time warping; graph edit distance; Milner and van Glabbeek on process equivalence; bisimulation and trace equivalence; van der Aalst on process mining; and measurement theory on admissible comparison. Candidate distinctions were retained only when counterexamples showed that collapsing them produced false conclusions. The proposed framework was then tested against seven cases: identical implementations, distinct interfaces over one system, GUI versus CLI, API versus conversation, novice versus expert, accessibility variants, and simulated versus observed interaction. The framework is descriptive. It does not prescribe a single metric or ranking. # 3. Why Similarity Is Not One Relation Similarity is not a property that exists independently of representation and purpose. Tversky showed that judged similarity can be modeled through common and distinctive features, that feature salience is context-sensitive, and that similarity judgments can be asymmetric. Metric-space models impose identity, symmetry, and triangle inequality, but many psychological and practical judgments violate one or more of these assumptions. Formal computer science reaches the same conclusion from another direction. Trace equivalence preserves possible observable action sequences. Bisimulation additionally preserves branching structure and stepwise matching. Testing equivalences preserve outcomes of specified tests. Observational equivalence depends on the contexts allowed to distinguish systems. The linear-time/branching-time spectrum demonstrates that there is no unique behavioral equivalence; relations are ordered by discriminating power. Process mining separates model-to-model similarity, log-to-log similarity, and conformance between logs and models. Sequence comparison distinguishes edit distance, alignment, temporal warping, subsequence similarity, and probabilistic distance. Graph comparison distinguishes exact isomorphism, subgraph matching, edit distance, spectral similarity, and kernel-based similarity. These are not alternative implementations of one universal relation. They preserve different structures and answer different explanatory questions. # 4. Canonical Distinctions Interaction token identity concerns whether two references denote the same historically situated episode. It requires continuity under the declared participant, boundary, and timescale criteria. Copying a log does not create a second interaction token; replaying the same inputs does. Interaction type identity concerns whether episodes instantiate the same declared type. Type membership depends on an abstraction function that suppresses some differences and preserves others. The same token can instantiate several types, such as authentication, error recovery, or turn-taking. Equivalence is a binary relation of exact preservation under a declared comparison contract. It is never unqualified. Semantic equivalence may preserve denotation or task-relevant consequences. Trace equivalence preserves observable sequences. Bisimulation preserves branching response structure. Opportunity equivalence preserves declared action-availability relations. Outcome equivalence preserves criterion outcomes. Similarity is graded proximity under declared dimensions, representations, alignment rules, metrics, weights, and tolerances. Similarity need not be symmetric when the comparison is directional, such as substitution, migration, or transfer. Incomparability is not low similarity. It occurs when no defensible common comparison space exists: boundaries conflict, required variables are absent, scales are noncommensurate, observation processes differ without calibration, uncertainty overwhelms discrimination, or the proposed mapping changes the target itself. # 5. Similarity Ontology The minimal ontology contains: Comparison target: the entity being compared, such as episode token, interaction type, protocol, opportunity profile, trace, behavior pattern, policy, strategy, outcome, or causal model. Comparison frame: declared system boundary, participants, initial conditions, task, environment, timescale, and observation window. Representation: the form in which each target is available for comparison. Correspondence mapping: a relation aligning entities, states, actions, events, roles, or features across targets. Invariant set: properties required to remain exact. Variant set: properties permitted to differ. Admissible transformation: a transformation treated as irrelevant for the comparison, such as renaming, temporal rescaling, stuttering, reordering of independent events, or modality substitution. Observable set: distinctions available to the declared observer or instrument. Distance or discrepancy: a typed measure of deviation. Weighting and tolerance: importance assignments and thresholds for equivalence or practical similarity. Uncertainty: error, missingness, model uncertainty, and confidence attached to inputs and results. Validity domain: population, tasks, systems, contexts, and purposes over which the comparison claim is supported. # 6. Typed Dimensions of Interaction Comparison Semantic comparison asks whether operations, states, relations, or consequences denote the same declared target. It does not establish identical access, behavior, or outcomes. Structural comparison concerns participants, coupling topology, state-transition structure, causal ordering, concurrency, branching, loops, and dependencies. Protocol comparison concerns permitted messages or actions, sequencing rules, preconditions, responses, completion, and failure behavior. Opportunity comparison concerns possible, capable, permitted, enabled, reachable, exposed, signaled, believed, reversible, and recoverable actions. Equality of backend actions does not establish opportunity equivalence. Trace comparison concerns recorded or attributed event sequences or partial orders. It is observation-model dependent and may use edit operations, alignments, temporal normalization, or probabilistic distances. Behavioral comparison concerns attributed trajectories or patterns, not raw records. It requires compatible segmentation and attribution rules. Policy comparison concerns mappings from states or beliefs to action distributions. Strategy comparison concerns higher-level organization across contingencies and may remain latent even when policies are estimated. Outcome comparison concerns declared success, utility, quality, safety, or other criteria. Equal outcomes do not imply equal process, opportunity, behavior, effort, or risk. Causal comparison concerns whether the same dependency structure or mechanism generated observations. It cannot be inferred from trace similarity alone. Measurement-relative comparison concerns whether two measured values are comparable under compatible instruments, scales, invariance assumptions, and uncertainty budgets. # 7. Equivalence Hierarchy The framework does not impose one total hierarchy because several dimensions are orthogonal. Within formal behavior, stronger relations generally imply weaker ones under fixed models: identity implies isomorphism under the chosen representation; isomorphism may imply bisimulation; bisimulation commonly implies trace equivalence; trace equivalence may imply equality of a selected outcome. The converses generally fail. Across interaction dimensions, no universal implication holds. Semantic equivalence does not imply opportunity equivalence. Opportunity equivalence does not imply behavioral equivalence because agents differ. Behavioral equivalence does not imply causal equivalence. Outcome equivalence does not imply behavioral or interactional equivalence. Measurement equivalence is a precondition for empirical comparison, not a property of the interactions themselves. The resulting architecture is a lattice of typed equivalence claims rather than a single ladder. A complete comparison report is therefore a vector of supported relations and distances, with explicit unknown or incomparable entries. # 8. Formal Comparison Contract Let interactions I and J be represented under contracts C_I and C_J. A comparison specification is: K = \ where T is the target type; F is the aligned comparison frame; M is the correspondence mapping; O is the observable set; A is the admissible transformation set; D is a family of typed distances or predicates; W is weighting; epsilon is the tolerance or equivalence bound; U is uncertainty; and V is the validity domain. Exact equivalence on dimension k holds when, after an admissible transformation and valid correspondence, all required observables are preserved and d_k(I,J)=0 or satisfies the formal equality predicate. Approximate equivalence holds when the distance and its uncertainty interval remain within epsilon_k. Similarity is the reported distance profile rather than a categorical assertion. Incomparability holds when the mapping, frame, observation model, or scale conditions required by K cannot be justified. A composite similarity score may be reported only when aggregation has a defensible measurement model. Weighted sums conceal compensation: severe inequality in permission or accessibility can be offset numerically by superficial trace similarity. The default output should therefore be a typed profile, not one scalar. # 9. Evidence and Measurement Requirements A comparison claim must identify its evidence level. Direct records include timestamps, messages, state snapshots, and instrument readings. Detected events are produced by segmentation or recognition rules. Attributed interaction and behavioral events add system or agent attribution. Policies, strategies, intentions, and causal mechanisms are inferred constructs. Trace similarity is invalid when logging coverage differs materially. Behavioral similarity is invalid when segmentation or attribution rules differ without calibration. Group comparison is invalid when measurement invariance is untested. Cross-modality comparison is invalid when metrics encode modality-specific costs but are interpreted as general interaction cost. Uncertainty should propagate through alignment, missing data, classification, metric estimation, and aggregation. A difference smaller than measurement uncertainty supports neither similarity nor dissimilarity. Reproducibility requires the target representations, mappings, code, parameterization, thresholds, exclusions, and sensitivity analyses to be available. # 10. Comparative Cases Identical implementations. Two episodes on the same software are not token-identical and need not be type-equivalent if initial state, authority, task, or participants differ. Implementation identity is weak evidence. Different interfaces over one system. A GUI and CLI may be semantically equivalent at the operation layer while differing in exposure, signaling, sequence cost, recoverability, and trace distributions. Similarity must be reported by dimension. API versus conversational interface. Both may invoke the same operation, but the conversation can introduce ambiguity, overclaim, confirmation structure, and nondeterministic interpretation. Backend outcome equivalence does not establish protocol or opportunity equivalence. Novice versus expert. The projection and system-relative opportunity sets may be identical. Believed actions, strategies, search behavior, and recovery differ. The comparison target determines whether this is one interaction type with participant variation or different types. Accessibility variants. Visual, auditory, and tactile projections can preserve semantics and completion while changing ordering, latency, memory burden, spatial comparison, and error recovery. Modality substitution is admissible only for explicitly preserved dimensions. Simulated versus observed interaction. Simulation can reproduce traces or aggregate distributions without reproducing causal mechanisms, situated interpretation, or measurement error. Validation must distinguish trace fidelity, distributional fidelity, policy fidelity, and causal fidelity. # 11. Admissible Transformations Renaming is admissible for structural and protocol comparison when labels have a validated correspondence and no semantics are carried by the names. Temporal translation is often admissible; temporal scaling is admissible only when absolute timing is not part of the target. Dynamic time warping may align patterns while concealing meaningful latency differences. Stuttering or insertion of silent internal steps is admissible under weak behavioral equivalences when internal events are legitimately unobservable. It is not admissible when those steps affect effort, risk, energy, or recovery. Reordering independent concurrent events is admissible under partial-order comparison when independence is established. Sequence metrics can falsely penalize equivalent concurrency. Aggregation is admissible only when the coarse-graining preserves required invariants. Segmentation changes can manufacture similarity or difference. Modality substitution is admissible for operation semantics under a valid cross-modal mapping, but not automatically for perceptual, temporal, behavioral, or accessibility comparison. Implementation substitution is admissible when the comparison target is defined above implementation and equivalence obligations are verified. Identical output samples are insufficient. # 12. Comparison Protocol 1\. Declare whether the objects are episode tokens, types, models, traces, behaviors, opportunities, policies, strategies, outcomes, or mechanisms.\ 2. Establish compatible interaction boundaries, participants, tasks, initial conditions, and timescales.\ 3. Specify representations and observation models; audit missingness and logging coverage.\ 4. Define the correspondence mapping across states, actions, events, roles, and outcomes.\ 5. Select dimensions independently; do not infer one from another.\ 6. Declare invariants, admissible transformations, and prohibited transformations.\ 7. Choose metrics or formal predicates with scale assumptions and known failure modes.\ 8. Set tolerances before inspecting results where confirmatory claims are intended.\ 9. Propagate measurement and model uncertainty.\ 10. Report a typed comparison profile with equivalence, similarity, difference, unknown, or incomparable for each dimension.\ 11. Test robustness to alternative boundaries, mappings, metrics, weights, and segmentation.\ 12. State the validity domain and prohibited generalizations. # 13. Falsification Tests The theory should be narrowed or rejected if a single established equivalence relation can represent all relevant interaction comparisons without losing distinctions among semantics, protocol, opportunity, trace, behavior, policy, outcome, cause, and measurement. Current literature strongly contradicts that possibility. The typed framework loses value if its dimensions cannot be measured reliably, if independent analysts cannot reproduce correspondence and segmentation decisions, or if typed profiles add no explanatory or predictive value beyond a well-chosen single metric. The proposed incomparability category is falsified as practically necessary if every studied comparison can be defensibly embedded in a common space without arbitrary assumptions. Conversely, frequent analyst disagreement about mappings and boundaries would weaken claims of stable equivalence. Claims of opportunity, behavioral, policy, or causal similarity must be rejected when based only on semantic or trace evidence. A composite score should be rejected when conclusions reverse under plausible weighting or when compensation masks a critical dimension. # 14. Threats to Validity The main threat is framework breadth. Typed comparison can become a checklist rather than a theory if dimensions are added without mechanisms or formal relations. The framework therefore limits itself to distinctions already supported across formal, behavioral, and measurement literatures. Correspondence mappings can encode the conclusion. Analysts may align only convenient events or choose abstractions that manufacture equivalence. Pre-registration, independent coding, mapping audits, and sensitivity analysis are required. Human interaction involves context, meaning, and evolving goals that cannot always be reduced to fixed feature vectors or transition systems. Strategy and causal similarity may remain underidentified. Cross-cultural and accessibility comparisons are especially vulnerable to treating instrument bias as participant difference. Exact equivalence can be undecidable or computationally expensive for expressive models. Approximation introduces tolerance dependence. Empirical logs are finite samples and cannot prove equality of full behavior spaces. # 15. Implications for Interaction Research Similarity should not be treated as a single dependent variable. Research should ask which equivalence or distance relation is scientifically relevant to the claim. Interface migration may require semantic and opportunity preservation; accessibility evaluation may require outcome preservation without demanding trace identity; behavioral transfer may require type-level structural similarity while allowing different surface actions; formal verification may require bisimulation or refinement. The framework also clarifies the next research stage. Transfer depends on a declared similarity relation between source and target interactions. Strategy research requires separation of trace similarity from latent organizational similarity. Formal-model selection requires identifying which equivalences the model can express and decide. Comparative interaction can then use typed profiles rather than ungrounded rankings. # 16. Conclusion The evidence supports a general theory of interaction comparison, but not a universal similarity metric. Interaction identity, equivalence, similarity, and incomparability are distinct. Every defensible claim is relative to a declared target, frame, representation, correspondence, observable set, admissible transformations, dimensions, metrics, tolerances, uncertainty model, and validity domain. Existing literatures already supply the constituent formal and empirical tools. The needed contribution is a cross-disciplinary integration that prevents semantic, structural, opportunity, trace, behavioral, policy, outcome, causal, and measurement relations from being collapsed. The canonical output is a typed similarity profile. Scalar aggregation is optional and requires independent justification. # 17. Reusable Artifacts ## A. Similarity Ontology ----------------------------------------------------------------------- **Element** **Definition** ----------------------------------- ----------------------------------- Comparison target The entity or construct being compared. Comparison frame Boundary, participants, task, state, environment, and timescale. Representation The form available to the comparison procedure. Correspondence mapping Alignment across states, events, actions, roles, or features. Invariant Property required to remain exact. Admissible transformation Difference treated as irrelevant for a declared comparison. Observable set Distinctions available to an observer, instrument, or test context. Distance/predicate Typed rule used to determine discrepancy or equivalence. Tolerance Maximum admissible discrepancy for approximate equivalence. Uncertainty Error and indeterminacy in records, mappings, measures, and models. Validity domain Scope over which the comparison claim is supported. Incomparability Failure to establish a defensible common comparison space. ----------------------------------------------------------------------- ## B. Similarity Taxonomy ------------------------------------------------------------------------ **Type** **Preserved target** **Required evidence** ----------------------- ----------------------- ------------------------ Token identity Historical continuity Interaction contract, of one bounded episode provenance Type identity Instantiation of the Classification rules same abstraction-defined type Semantic Denotation, operation Formal semantics, task meaning, inferential contract consequences Structural Topology, dependencies, Graphs, transition branching, concurrency systems Protocol Sequencing, Protocol/state-machine preconditions, model responses, completion Opportunity Feasible, permitted, Opportunity contract exposed, signaled, believed, recoverable actions Trace Recorded or attributed Trace model and event order and timing observation contract Behavioral Attributed trajectory Behavioral evidence or pattern contract Policy State/belief to action Policy estimates or distribution model Strategy Higher-order Multi-episode evidence organization across contingencies Outcome Declared criterion Outcome contract results Causal Generating dependency Intervention/causal or mechanism evidence Measurement-relative Comparability of Measurement invariance measured quantities and uncertainty ------------------------------------------------------------------------ ## C. Interaction Equivalence Hierarchy ----------------------------------------------------------------------- **Relation** **Required sameness** **Observation basis** ----------------------- ----------------------- ----------------------- Token identity Same historical episode Boundary continuity and provenance Isomorphism Same structure up to Exact structural bijective renaming mapping Bisimulation Stepwise matching Transition relation including branching Trace equivalence Same observable traces Trace language Testing/observational No allowed test/context Declared test contexts equivalence distinguishes systems Semantic equivalence Same denotation or Semantic contract declared semantic consequences Opportunity equivalence Same typed opportunity Opportunity dimensions profile Behavioral equivalence Same attributed Behavioral variables behavior under observation contract Policy equivalence Same action Policy mapping distributions under aligned states/beliefs Outcome equivalence Same declared criterion Outcome metric distribution Approximate equivalence Typed distance within Metric plus epsilon tolerance and uncertainty Incomparability No justified common Failed space alignment/validity conditions ----------------------------------------------------------------------- ## D. Similarity Contract - Comparison identifier and purpose - Target types and token/type status - Interaction contracts and aligned boundaries - Participants, tasks, environments, initial conditions, and timescales - Representations and observation models - Correspondence mapping and mapping evidence - Required invariants and permitted variants - Admissible and prohibited transformations - Comparison dimensions - Formal predicates, metrics, scales, and parameters - Weights and aggregation model, if any - Equivalence tolerances and decision rules - Missingness and uncertainty budget - Sensitivity analyses - Evidence level for each claim - Validity domain and prohibited generalizations - Final typed profile: equivalent, approximately equivalent, different, unknown, or incomparable by dimension ## E. Similarity Comparison Protocol 1\. Declare whether the objects are episode tokens, types, models, traces, behaviors, opportunities, policies, strategies, outcomes, or mechanisms. 2\. Establish compatible interaction boundaries, participants, tasks, initial conditions, and timescales. 3\. Specify representations and observation models; audit missingness and logging coverage. 4\. Define the correspondence mapping across states, actions, events, roles, and outcomes. 5\. Select dimensions independently; do not infer one from another. 6\. Declare invariants, admissible transformations, and prohibited transformations. 7\. Choose metrics or formal predicates with scale assumptions and known failure modes. 8\. Set tolerances before inspecting results where confirmatory claims are intended. 9\. Propagate measurement and model uncertainty. 10\. Report a typed comparison profile with equivalence, similarity, difference, unknown, or incomparable for each dimension. 11\. Test robustness to alternative boundaries, mappings, metrics, weights, and segmentation. 12\. State the validity domain and prohibited generalizations. ## F. Admissible Transformation Matrix --------------------------------------------------------------------------------------------- **Transformation** **Candidate **Admissible?** **Principal dimensions** constraint** ----------------------------- --------------------- ----------------- ----------------------- Label renaming Structural/protocol Yes, with No if labels carry bijection semantic or signaling content Time translation Trace/behavior Usually No when calendar position matters Time scaling Pattern/strategy Conditional No when absolute latency is a target Dynamic time warping Temporal pattern Conditional Can conceal meaningful delay Silent-step insertion Weak behavioral Conditional No when internal work equivalence affects cost/risk Independent-event reordering Partial-order Yes if No if order has behavior independence causal/semantic force proven Aggregation/coarse-graining Type/structural Conditional Must preserve declared invariants Modality substitution Semantic/outcome Conditional Not automatically perceptual/behavioral equivalent Implementation substitution Semantic/protocol Conditional Requires verified obligations Participant substitution Type-level comparison Conditional Not token identity; observer assumptions change --------------------------------------------------------------------------------------------- ## G. Falsification Matrix ------------------------------------------------------------------------ **Claim/test** **Falsifying evidence** **Consequence** ----------------------- ------------------------ ----------------------- F1 Universal relation One established relation Remove typed framework captures all comparison and adopt it dimensions without loss F2 Unreliable Opportunity, behavior, Restrict framework to dimensions or strategy dimensions reliable dimensions cannot be measured reproducibly F3 No added value Typed profile gives no Prefer the simpler explanatory/predictive metric gain over one metric F4 Arbitrary mappings Independent analysts Treat claims as cannot agree on analyst-relative or correspondence under incomparable explicit rules F5 Incomparability All cases admit Remove incomparability unnecessary justified common spaces as a primitive status F6 Aggregation Composite conclusions Reject scalar summary robustness reverse under plausible weights F7 Trace sufficiency Trace similarity Collapse higher predicts every relevant dimensions where comparison outcome demonstrated F8 Cross-context Measurement relations do Limit validity domain invariance failure not remain invariant across groups/modalities ------------------------------------------------------------------------ # 18. References Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327-352. Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science, 237, 1317-1323. Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady, 10, 707-710. Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49. Sanfeliu, A., & Fu, K. S. (1983). A distance measure between attributed relational graphs for pattern recognition. IEEE Transactions on Systems, Man, and Cybernetics, 13(3), 353-362. Bunke, H. (1997). On a relation between graph edit distance and maximum common subgraph. Pattern Recognition Letters, 18, 689-694. Milner, R. (1989). Communication and Concurrency. Prentice Hall. van Glabbeek, R. J. (1990). The linear time-branching time spectrum. In CONCUR 1990. Springer. Park, D. (1981). Concurrency and automata on infinite sequences. In Theoretical Computer Science. Springer. Lange, M., Lozes, E., & Vargas Guzman, M. (2013). Model-checking process equivalences. Theoretical Computer Science, 560, 326-347. Abate, A., Bacci, G., Bacci, G., & Larsen, K. G. (2017). On the relationship between bisimulation and trace equivalence in an approximate probabilistic context. van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action (2nd ed.). Springer. Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions. García-Bañuelos, L., van Beest, N. R. T. P., Dumas, M., La Rosa, M., & Mertens, W. (2018). Complete and interpretable conformance checking of business processes. IEEE Transactions on Software Engineering, 44(3), 262-290. Suppes, P., Krantz, D. H., Luce, R. D., & Tversky, A. (1989). Foundations of Measurement, Vol. II. Academic Press. Kruskal, J. B., & Wish, M. (1978). Multidimensional Scaling. Sage. Gower, J. C. (1971). A general coefficient of similarity and some of its properties. Biometrics, 27, 857-871. Rosenbaum, P. R. (2020). Design of Observational Studies (2nd ed.). Springer. ISO 9241-11:2018. Ergonomics of human-system interaction - Usability: Definitions and concepts. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press. ======================================================================== ## FILE: docs/02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.md (630 lines, 27.7 KiB) ======================================================================== **Interaction Transfer** *Toward a Theory of Experience and Adaptation* Cross-disciplinary research paper # Abstract Interaction transfer is the influence of prior interaction experience on performance, interpretation, opportunity recognition, strategy, or learning in a later interaction under changed conditions. It is not synonymous with learning, familiarity, repetition, expertise, or successful generalization. Learning is change attributable to experience; transfer is evidence that some consequence of prior experience affects a distinct target context. Familiarity denotes prior exposure and may produce fluency without transferable structure. Expertise is durable, organized performance within a domain and may remain highly context-specific. Across cognitive psychology, learning sciences, skill acquisition, expertise research, reinforcement learning, transfer learning, activity theory, distributed cognition, and HCI, existing theories provide the required mechanisms: common elements, abstraction, analogical mapping, schema induction, procedural compilation, policy reuse, representation alignment, retrieval, contextual cueing, habit, metacognitive control, and socially distributed practice. No new mental substance called interaction memory is required. What is missing is a shared interaction-level contract that specifies the source episode, target episode, transferred content, mediating mechanism, preserved relations, context shift, measurement model, and counterfactual evidence. The paper therefore concludes that existing theories are sufficient but require a typed cross-disciplinary transfer framework. The proposed model represents experience as changes to agent, artifact, environment, and coordination state. Transfer is classified by what changes, where it is expressed, its direction, distance, durability, intentionality, and dependence on representation. The reusable artifacts include a transfer ontology, adaptation model, transfer taxonomy, interaction-experience model, metric registry, transfer contract, comparison protocol, and falsification matrix. # 1. Problem Statement Prior interaction often changes later interaction, but the phrase "experience transfers" compresses several different claims. A person may become faster because the same motor sequence is repeated, may recognize a structurally similar command in a new interface, may reuse a strategy across software families, may apply an inappropriate habit, or may reconstruct a solution through analogy. An artificial agent may initialize a policy from a related task, reuse a representation, or exploit shared dynamics. A team may retain coordination routines in artifacts and procedures rather than in any single member. A scientific theory must therefore answer four questions separately: what changed because of the source interaction; what component of that change was available in the target; what relation between source and target licensed reuse; and what evidence shows that target behavior depended on the source rather than on baseline ability, repeated exposure, task similarity, or measurement artifact. # 2. Method and Scope The review used concept comparison rather than disciplinary summary. Foundational accounts of transfer, skill, expertise, analogy, situated learning, reinforcement learning, transfer learning, distributed cognition, and HCI migration were compared by their units, mechanisms, boundary conditions, and evidence requirements. The analysis treated the completed Interaction, Behavior, Measurement, Opportunity, Representation, and Similarity frameworks as constraints, not as evidence that a new construct is needed. The main falsification question was whether "interaction transfer" adds explanatory content beyond existing theories. The candidate framework was retained only where it coordinates distinctions that established theories already support but do not jointly expose. # 3. Existing Theories of Transfer ## 3.1 Common elements and structural overlap Thorndike and Woodworth's identical-elements tradition explains transfer through overlap between source and target demands. Later cognitive accounts replace literal stimulus identity with shared productions, procedures, relations, or representational components. This family explains why near transfer is common and why far transfer is difficult. Its limit is that "shared element" depends on the level of representation: two interfaces can differ visually while preserving an operation grammar, or appear similar while implementing different semantics. ## 3.2 Abstraction, schema, and analogy Schema and analogical-transfer theories explain reuse when a learner abstracts relational structure from examples, retrieves a relevant source, maps corresponding relations, and adapts the solution. Transfer may fail at retrieval even when a useful analogy exists, or fail at mapping when superficial similarity dominates. Representation therefore affects transfer by changing which invariants are salient and recoverable, not by directly determining behavior. ## 3.3 Skill acquisition and procedural knowledge Skill theories distinguish declarative knowledge, proceduralization, compilation, chunking, automaticity, and adaptive control. Practice can reduce time and error while narrowing flexibility. Procedural knowledge transfers when target conditions preserve relevant productions or control structures; automatic habits can create negative transfer when changed contingencies are not detected. ## 3.4 Expertise Expertise reorganizes perception, memory, diagnosis, and strategy around domain-relevant structure. Experts notice relations that novices miss, but expert performance is not a general transferable capacity. It is often conditional on representative tasks, feedback histories, and domain-specific knowledge. Expertise must therefore be measured as a profile of calibrated performance and representation, not inferred from tenure or status. ## 3.5 Reinforcement learning and transfer learning Reinforcement learning formalizes transfer through reused value functions, policies, representations, options, models, demonstrations, or successor features. Machine-learning transfer theory separates source and target domains and tasks, and recognizes negative transfer when reused structure harms target performance. These formalisms are precise about optimization but often abstract away human interpretation, cultural practice, artifact mediation, and discoverability. ## 3.6 Situated, activity, and distributed accounts Situated and activity theories challenge the assumption that transferable knowledge is an internal package carried unchanged between contexts. What persists may be participation, routines, artifact configurations, conventions, or access to distributed resources. Transfer can be a transformation of participation or coordination rather than retrieval of an invariant internal representation. A general framework must therefore permit agent-internal, artifact-mediated, social, and environmental carriers. # 4. Canonical Distinctions Learning is a relatively durable change in capability, representation, policy, or behavior attributable to experience. Transfer is a source-dependent difference in a target context that is not identical to the learning context. Adaptation is change that improves or regulates fit to current conditions; it may arise without transfer from a distinct source. Familiarity is prior exposure to a person, representation, operation, or context; it is a predictor, not a mechanism or outcome. Practice is repeated performance. Expertise is organized, reliable, and often efficient performance within a domain. Habit is cue-dependent action tendency strengthened by repetition. Generalization is extension of a learned function to unobserved cases and is one formal species of transfer. Retention concerns persistence over time without requiring contextual change. # 5. What Transfers? The literature does not support one transferable entity. At least eight carrier types recur: - Perceptual attunement: sensitivity to cues, invariants, or diagnostic structure. - Semantic knowledge: concepts, relations, rules, and causal models. - Procedures and skills: action sequences, productions, motor programs, and operation grammars. - Strategies and policies: conditional organization of actions under goals and contingencies. - Expectations and beliefs: anticipated availability, consequence, risk, and reversibility. - Values and preferences: learned utility, cost, confidence, and avoidance structure. - Externalized structure: notes, templates, macros, layouts, documentation, and shared artifacts. - Coordination practices: roles, conventions, communication routines, and division of labor. These carriers can transfer independently. A user may retain semantic knowledge but lose motor fluency after modality migration; preserve a strategy while relearning commands; retain a habit that becomes harmful; or use an external artifact without internal recall. # 6. Interaction Experience Model An interaction experience is represented as an update, not merely an episode record. Let an experience update be: ΔE = ⟨ΔK, ΔP, ΔB, ΔV, ΔH, ΔA, ΔC, ΔM, U⟩ where ΔK is change in semantic or causal knowledge; ΔP is procedural or policy change; ΔB is change in beliefs about actions and consequences; ΔV is value or preference change; ΔH is habit strength; ΔA is perceptual attunement; ΔC is change in coordination practices; ΔM is change to external memory or artifacts; and U records uncertainty and attribution. The source interaction does not deposit a complete transferable object. It changes a distributed experience state spanning agent, artifacts, environment, and social organization. A later target interaction recruits some subset of that state under target cues and constraints. # 7. Candidate Adaptation Model Transfer from source S to target T is modeled as a sequence: 1\. Acquisition: source interaction changes one or more experience-state components.\ 2. Retention: some change persists until the target episode.\ 3. Access: target cues, goals, or deliberate search activate relevant prior structure.\ 4. Correspondence: source and target elements or relations are aligned.\ 5. Reuse: prior knowledge, procedure, policy, artifact, or coordination routine is applied.\ 6. Adaptation: reused structure is modified for target constraints.\ 7. Evaluation: feedback reveals fit, mismatch, or uncertainty.\ 8. Consolidation or revision: the experience state is strengthened, differentiated, suppressed, or reorganized. Transfer success is therefore conjunctive. Failure can arise from absence of learning, decay, retrieval failure, poor correspondence, rigid reuse, inadequate opportunity, altered authority, incompatible representation, or misleading feedback. # 8. Formal Definition Let S and T be source and target interaction contexts under declared similarity and measurement contracts. Let Y_T be a target measure and do(S=1) denote exposure to the source experience. Transfer exists for population or agent x when: τ = E\[Y_T \| do(S=1)\] - E\[Y_T \| do(S=0)\] ≠ 0 and the target differs from the source on at least one declared contextual or representational dimension. Positive transfer has τ in the desired direction; negative transfer has τ in the harmful direction; null transfer is compatible with learning when source gains do not affect the target. Mechanistic transfer claims additionally require evidence that a specified carrier or mediator changed after S, was available or retrieved in T, and accounted for part of τ under plausible alternatives. Observed target superiority alone establishes neither the mechanism nor the transferred content. # 9. Transfer Taxonomy Transfer should be typed along independent axes rather than labeled simply near or far: ----------------------------------------------------------------------- **Axis** **Values** **Question** ----------------------- ----------------------- ----------------------- Direction positive, negative, Did prior experience null, mixed help, harm, or have heterogeneous effects? Distance declared Across what changes in multidimensional task, representation, source-target modality, device, difference domain, time, and social context? Carrier knowledge, procedure, What consequence of policy, belief, value, experience was reused? habit, attunement, artifact, coordination Access spontaneous, cued, How was prior structure prompted, instructed recruited? Level event, action, episode, At what behavioral strategy, practice organization was transfer expressed? Duration immediate, delayed, How long did the effect durable, decaying persist? Intentionality deliberate, incidental, Was transfer automatic consciously attempted? Distribution individual, Where was transferable artifact-mediated, structure carried? collective, environmental Specificity token, type, What invariant relational, supported principle-based correspondence? ----------------------------------------------------------------------- # 10. Comparative Cases ## 10.1 Interface migration Migration between software versions can preserve task semantics while changing layout, labels, shortcuts, or workflow. Semantic and strategic transfer may be positive, motor and habitual transfer negative, and discoverability reduced. "Familiar interface" is therefore not a unitary condition. ## 10.2 Modality migration Moving from visual to auditory or tactile interaction may preserve operations and outcomes while changing seriality, memory load, cue persistence, navigation, and error recovery. Transfer should be assessed separately for semantic knowledge, strategy, command vocabulary, spatial mapping, and timing. ## 10.3 Cross-device interaction Desktop, tablet, and mobile variants may share content and account state but differ in gesture vocabulary, screen real estate, interruption patterns, and exposed opportunity. Transfer depends on preserved operation grammar and representation cues, not brand identity alone. ## 10.4 Software families Shared conventions across applications can support rapid transfer of editing, navigation, and file-management procedures. False friends - identical symbols with different effects - produce negative transfer. Family resemblance must be decomposed into semantic, structural, opportunity, and protocol similarity. ## 10.5 Expert and novice Experts often transfer abstract relations and diagnostic cues, while novices rely on surface correspondence. Yet expertise can impair transfer when automated routines suppress detection of changed constraints. Group labels should be replaced by measured knowledge, strategy, calibration, and source exposure. ## 10.6 Repeated task performance Improvement on the same task establishes practice and retention, not transfer. A valid transfer test must alter at least one declared dimension and preserve a defensible basis for comparison. Otherwise source and target are repetitions of one condition. # 11. Measurement and Metrics Transfer measurement must inherit the Measurement Contract. The source and target constructs, observation models, scales, segmentation, uncertainty, and comparison frame must be declared. Recommended metrics include: - Target effect: controlled difference in target performance attributable to source exposure. - Transfer efficiency: target gain relative to source practice cost or exposure. - Savings: reduction in trials, time, or error needed to reach a criterion. - Generalization gradient: effect magnitude across declared source-target distances. - Belief transfer: change in precision, recall, and calibration of believed action sets. - Strategy reuse: probability of an inferred strategy under target contingencies, with uncertainty. - Negative-transfer cost: excess error, latency, recovery, or risk caused by inappropriate reuse. - Durability: transfer effect as a function of delay. - Adaptation rate: speed with which reused structure is revised after mismatch. - Representation sensitivity: interaction between source-target representation change and transfer. Self-report of usefulness is evidence about perceived transfer, not proof of behavioral transfer. Faster target performance may reflect familiarity, motor priming, motivation, selection, or common task ability. Mediation claims require temporally ordered carrier measurements and sensitivity analysis. # 12. Transfer Protocol 1\. Declare source and target interaction contracts.\ 2. Specify which target dimensions differ and which invariants license comparison.\ 3. Define the candidate carrier and mechanism before observing target outcomes.\ 4. Measure source learning separately from target transfer.\ 5. Include a no-source or alternative-source counterfactual.\ 6. Control prior exposure, baseline ability, motivation, device access, and opportunity structure.\ 7. Test immediate and delayed target performance where durability matters.\ 8. Measure positive, negative, and null outcomes, including recovery and strategy change.\ 9. Separate direct observations, derived features, latent carriers, and causal conclusions.\ 10. Report uncertainty, heterogeneity, exclusions, and boundary conditions.\ 11. Replicate across at least one additional target context before claiming generality. # 13. Falsification Matrix ----------------------------------------------------------------------- **Claim** **Evidence against** **Consequence** ----------------------- ----------------------- ----------------------- Interaction transfer Established learning Reject new primitive; needs a special and transfer models retain only primitive explain all observed coordination vocabulary effects with no loss Source-target Transfer is unrelated Revise similarity similarity predicts to declared dimensions or reject transfer similarities after overlap mechanism controls Belief mediates Belief change is Remove belief mediation interface transfer unreliable or does not claim predict target action Strategy reuse supports Target gains occur Treat outcome gain as far transfer without evidence of unexplained transfer strategy access or adaptation Distributed carriers Removing artifacts and Narrow framework to matter coordination resources agent-internal carriers leaves effects for that domain unchanged Transfer differs from Exposure-only controls Classify effect as familiarity explain the full target familiarity or effect repetition, not structural transfer Framework improves Typed variables add no Reduce framework to prediction held-out gain over descriptive taxonomy source exposure and target similarity ----------------------------------------------------------------------- # 14. Threats to Validity Transfer is unusually sensitive to source-target definition. Researchers can manufacture "far transfer" by describing contexts broadly or manufacture "near transfer" by choosing fine-grained dimensions. Distance must therefore be a declared vector, not an intuitive label. Selection and expectancy threaten causal inference: experienced users differ before the source episode, and participants may infer target hypotheses. Practice effects, regression, instrumentation change, and repeated testing can mimic transfer. Latent carriers such as strategy and schema are model-dependent and should not be inferred from one trace. The framework may privilege well-bounded computational tasks. Open-ended work, collective practice, and changing institutions can transform the target itself. In such cases transfer may be better described as recontextualization or development of activity rather than transport of stable content. # 15. Reusable Artifacts ## A. Transfer Ontology Entities: source interaction, target interaction, agent or collective, experience-state component, carrier, cue, correspondence, adaptation, outcome, artifact, context, delay, measurement model. Relations: acquired-in, retained-until, cued-by, corresponds-to, reused-in, adapted-for, mediated-by, expressed-as, improves, impairs, persists, decays, and is-measured-by. ## B. Transfer Contract Identity: source and target episode identifiers, boundaries, timescales, participants, and tasks.\ Source learning: experience component changed, evidence, magnitude, and uncertainty.\ Target shift: changed and preserved dimensions across semantic, structural, representational, opportunity, modality, device, social, and temporal axes.\ Carrier: knowledge, procedure, strategy, belief, value, habit, attunement, artifact, or coordination practice.\ Mechanism: retrieval, analogy, shared production, policy reuse, cueing, abstraction, compilation, or participation transformation.\ Outcome: direct measures, derived metrics, latent estimates, direction, durability, and heterogeneity.\ Counterfactual: control condition and assumptions supporting source attribution.\ Failure conditions: no source learning, no retention, access failure, mismatch, negative transfer, confounding, or measurement non-invariance. ## C. Experience Model Experience is represented as a versioned update to distributed state rather than as a scalar amount. Each update records source episode, affected component, direction, confidence, persistence estimate, contexts in which it has been expressed, and known failure conditions. ## D. Metric Registry -------------------------------------------------------------------------- **Metric** **Numerator / **Required **Prohibited estimand** controls** interpretation** ------------------- ----------------- ----------------- ------------------ Target transfer Counterfactual Baseline, prior Does not identify effect target difference exposure, target carrier opportunity Savings Trials/time saved Criterion Not generality by to criterion equivalence, itself practice dose Generalization Effect across Stable Distance is not gradient distance vector measurement and one-dimensional target difficulty Strategy reuse Posterior Trace Not directly probability or comparability, observed intention coded recurrence alternative strategies Negative-transfer Excess harm Target semantics Not evidence of cost relative to and feedback low ability control Durability Effect over delay Retention Immediate effect interval and is not durable intervening transfer experience -------------------------------------------------------------------------- # 16. Conclusion Existing theories of learning, transfer, expertise, adaptation, analogy, skill, reinforcement learning, and situated practice are sufficient to explain the known constituents of interaction transfer. The evidence does not justify a new primitive or a container called interaction memory. A cross-disciplinary synthesis is nevertheless warranted. Computational interaction research requires a typed account because representation, opportunity, semantic structure, motor procedure, strategy, belief, artifact support, and coordination can transfer differently. Transfer is best defined as a source-dependent difference expressed in a distinct target context under declared source-target relations and a valid counterfactual. The scientific burden is not to show that experienced agents perform differently, but to specify what changed, how it was accessed, why it applied, what was adapted, and which alternative explanations were excluded. # 17. References Thorndike, E. L., & Woodworth, R. S. (1901). The influence of improvement in one mental function upon the efficiency of other functions. Psychological Review. Judd, C. H. (1908). The relation of special training to general intelligence. Educational Review. Singley, M. K., & Anderson, J. R. (1989). The Transfer of Cognitive Skill. Harvard University Press. Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128(4), 612-637. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How People Learn. National Academies Press. National Academies of Sciences, Engineering, and Medicine. (2018). How People Learn II. National Academies Press. Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155-170. Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1-38. Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-406. Fitts, P. M., & Posner, M. I. (1967). Human Performance. Brooks/Cole. Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406. Lave, J. (1988). Cognition in Practice. Cambridge University Press. Greeno, J. G., Smith, D. R., & Moore, J. L. (1993). Transfer of situated learning. In Transfer on Trial. Beach, K. (1999). Consequential transitions: A sociocultural expedition beyond transfer in education. Review of Research in Education, 24, 101-139. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Engestrom, Y. (1987). Learning by Expanding. Orienta-Konsultit. Sutton, R. S., Precup, D., & Singh, S. (1999). Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211. Taylor, M. E., & Stone, P. (2009). Transfer learning for reinforcement learning domains: A survey. Journal of Machine Learning Research, 10, 1633-1685. Pan, S. J., & Yang, Q. (2010). A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359. Thorndike, R. L. (1949). Personnel Selection: Test and Measurement Techniques. Wiley. Norman, D. A. (2013). The Design of Everyday Things. Basic Books. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press. ======================================================================== ## FILE: docs/02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.md (836 lines, 34.7 KiB) ======================================================================== **Interaction Strategies** *Toward a Theory of Behavioral Organization* Foundational research paper # Abstract Strategy is widely invoked to explain organized behavior, yet the term is used inconsistently across planning, reinforcement learning, decision theory, cognitive science, robotics, and human-computer interaction. This paper asks what an interaction strategy is, how it differs from action, plan, policy, heuristic, skill, and intention, and how it can be inferred without treating it as directly observed. The cross-disciplinary evidence rejects three reductions: a strategy is not a single action, not a mere observed sequence, and not necessarily an explicit plan. A stable synthesis emerges. An interaction strategy is an inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a class of interaction states. Strategies may be deliberative or learned, explicit or tacit, deterministic or stochastic, individual or distributed, and stable or adaptive. They are supported by traces but are not identical with traces. The paper proposes a typed strategy ontology, a policy representation separating goals, beliefs, action rules, information-seeking, commitments, and revision conditions, a lifecycle model, an inference protocol, and an evidence hierarchy. It concludes that existing theories are sufficient in their constituent mechanisms, but interaction research requires a shared strategy-analysis framework to connect behavioral traces, opportunity structures, transfer, and formal models. # 1. Problem Statement Interaction research often explains repeated or coordinated behavior by naming a strategy: users "search systematically," "explore," "satisfice," "follow the interface," "reuse a workflow," or "recover by backtracking." Such claims are stronger than descriptions of traces. A trace records what occurred under an observation model. A strategy claims that behavior was organized by a persistent or recurring structure that selected, sequenced, or revised actions across contingencies. The central difficulty is evidential. The same trace may be generated by different strategies, and the same strategy may generate different traces when states, opportunities, costs, beliefs, or stochastic outcomes differ. A successful sequence does not prove advance planning. Repetition does not prove habit. A verbal explanation does not establish that the reported rule generated the observed behavior. Strategy must therefore be treated as a latent explanatory construct whose warrant depends on converging evidence and discriminating predictions. The scientific task is not to introduce a new psychological substance. It is to identify the minimum structure required to distinguish strategy from neighboring concepts and to state how strategy claims can be represented, compared, tested, and falsified across human and artificial agents. # 2. Review Method The review is concept-centered rather than historical. Foundational sources were selected from philosophy of action and planning, human problem solving, reinforcement learning, decision theory, robotics, situated cognition, and human-computer interaction. Each tradition was analyzed for: (1) its unit of organization; (2) whether the organization is represented as a plan, policy, rule, procedure, intention, skill, or emergent pattern; (3) whether the construct is explicit or latent; (4) how it relates to goals and contingencies; (5) how it changes; and (6) what evidence identifies it. The synthesis was accepted only where distinctions survived cross-domain counterexamples. Candidate definitions were rejected if they made every repeated behavior strategic, required conscious planning, collapsed strategy into policy, or could not distinguish a strategy from a post hoc description. The final framework inherits the prior research program's separation between interaction episodes, behavioral traces, opportunity profiles, measurement claims, and transfer effects. # 3. Existing Traditions Planning theories treat plans as structures that organize future conduct. Bratman's planning theory emphasizes that intentions and partial plans coordinate activity over time by constraining later deliberation and supporting stability, while allowing reconsideration. Cohen and Levesque formalize intention through commitment conditions, showing why a plan that is merely represented differs from one adopted for action. Human problem-solving research represents organized behavior through problem spaces, operators, goals, subgoals, heuristics, and means-ends analysis. In this tradition, strategies are often higher-level regularities in search or problem decomposition rather than fixed action strings. Representation affects which strategies are available or efficient. Reinforcement learning provides a precise policy concept: a mapping from states or observations to action distributions. Hierarchical reinforcement learning adds temporally extended options consisting of initiation conditions, internal policies, and termination conditions. These formalisms capture conditional action selection and temporal abstraction, but a complete interaction strategy may also include information-seeking, commitment, switching rules, resource constraints, and socially distributed coordination. Decision theory explains action selection through preferences, beliefs, utilities, and constraints. Heuristics and bounded rationality explain organized departures from exhaustive optimization under limited time, information, and computation. A heuristic may be a component of a strategy, but strategies can coordinate multiple heuristics and include rules for choosing among them. Situated-action research rejects the claim that plans fully determine conduct. Plans may orient, account for, or retrospectively render action intelligible, while actual conduct remains responsive to local contingencies. This critique does not eliminate strategy; it constrains strategy models to remain conditional, revisable, and situated. Robotics separates high-level task planning from low-level control and increasingly integrates discrete plans with continuous motion, uncertainty, and risk. These systems demonstrate that strategic organization may span multiple representational and temporal levels. HCI uses strategy to describe search, navigation, command use, error recovery, exploration, and expert procedure. GOMS and related cognitive models distinguish goals, operators, methods, and selection rules. Their strength is operational decomposition; their limitation is that they can overstate stability when strategies are inferred from sparse or highly constrained tasks. # 4. Canonical Distinctions Action is a bounded event or attributed control contribution. A strategy organizes the conditional selection and composition of actions across more than one possible state or contingency. A plan is a prospective representation of intended organization. A strategy can be implemented without an explicit plan, and an explicit plan may never be adopted or executed. A policy is a formal or functional mapping from state or observation to action distribution. A strategy may contain a policy, but often also includes state abstraction, information acquisition, commitment, stopping, switching, recovery, and revision rules. A heuristic is a simplifying rule or procedure used under limited resources. It can be one component of a strategy. A skill is a learned capacity for reliable performance. A strategy selects and coordinates skills; a skill can also embody strategic structure at a lower level. A procedure specifies an ordered or conditional method. Strategies may invoke procedures but also decide when to depart from them. An intention is a commitment-bearing practical attitude. Intention can stabilize a strategy, but strategies need not be conscious or intention-based. A habit is a learned tendency triggered by context with reduced deliberative dependence. Habit may implement a strategy historically but can persist after the original criterion or context changes. A tactic is a locally selected maneuver within a broader strategy. The distinction is relative to temporal and organizational scale. A strategy is therefore not identified by explicitness, optimality, consciousness, success, or fixedness. Its defining role is organization across contingencies. # 5. Canonical Definition An interaction strategy is an inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response that tends to preserve or improve one or more criteria across a declared class of interaction states. Each clause is necessary. "Inferred" separates strategy from direct observation. "Temporally extended" excludes isolated actions. "Organization" requires relations among choices rather than mere recurrence. "Conditional" requires sensitivity to state, observation, belief, or contingency. "Information use" permits strategies whose primary function is search, diagnosis, or uncertainty reduction. "Resource allocation" includes time, effort, risk, attention, computation, and collaboration. "Contingency response" excludes rigid scripts that cannot handle variation unless rigidity itself is the declared strategy. "Criteria" avoids assuming a single explicit goal or utility. "Declared class of states" specifies the scope over which the strategy claim is intended to hold. The definition is implementation-independent. It applies to humans, artificial agents, teams, and hybrid systems while allowing their internal mechanisms to differ. # 6. Strategy Ontology The minimum ontology contains the following entities and relations. Agent or strategy-bearing system: the individual, artificial agent, team, or distributed arrangement to which the strategy is attributed. Interaction domain: the class of situations and coupling structures within which the strategy is claimed to operate. State and observation: the actual or estimated conditions relevant to selection. State need not be fully observable. Opportunity profile: feasible, permitted, exposed, signaled, believed, and recoverable actions available under declared conditions. Criterion set: goals, constraints, values, risks, deadlines, social commitments, or satisficing thresholds used to evaluate continuation or revision. Action repertoire: primitive or temporally extended actions available to the strategy. State abstraction: the distinctions the strategy treats as relevant. Two agents may face the same system state but organize behavior differently because they use different abstractions. Selection rule: a deterministic, stochastic, heuristic, or deliberative relation connecting represented conditions to action. Information policy: rules for observing, searching, querying, testing, or delegating before acting. Commitment structure: conditions under which prior choices constrain later deliberation. Contingency rule: responses to uncertainty, failure, interruption, or unanticipated state. Switching and stopping rule: conditions for abandoning, changing, suspending, or completing the strategy. Execution resources: time, attention, memory, computation, tools, collaborators, and authority. Outcome and feedback: consequences that update beliefs, skills, habits, or future strategies. Evidence base: records, traces, elicitation, interventions, and model comparisons supporting the attribution. # 7. Strategy Taxonomy Strategies should be typed along independent dimensions rather than placed in one exclusive hierarchy. By control form: open-loop, closed-loop, receding-horizon, event-triggered, or mixed. By representation: explicit symbolic plan, procedural rule, learned policy, heuristic bundle, reactive controller, or distributed coordination pattern. By uncertainty handling: certainty-equivalent, information-seeking, risk-sensitive, robust, exploratory, or adaptive. By temporal organization: immediate, episodic, hierarchical, persistent, or developmental. By selection regime: deterministic, stochastic, satisficing, optimizing, lexicographic, threshold-based, or convention-based. By revision: fixed, parameter-adaptive, structure-adaptive, opportunistic, or reflective. By social organization: individual, delegated, negotiated, role-based, jointly committed, or emergent-distributed. By learning relation: preconfigured, acquired, transferred, composed, imitated, or self-discovered. By evidential status: hypothesized, weakly supported, discriminated from named rivals, causally supported, or formally verified for an artificial system. # 8. Policy Representation A reusable strategy representation is: Sigma = \ D: declared interaction domain and scope.\ X: relevant system and environment state space.\ O: observation model.\ Z: strategy's state abstraction or belief representation.\ C: criteria and constraints.\ A: primitive and temporally extended action repertoire.\ pi: conditional action-selection policy.\ q: information-acquisition policy.\ k: commitment and persistence rules.\ r: recovery and contingency rules.\ w: switching rules among substrategies.\ tau: stopping and completion conditions.\ rho: resource model.\ U: uncertainty over model components and strategy attribution. This representation does not assert that a human internally stores an explicit tuple. It is an analytical contract. Components may be implemented neurally, symbolically, socially, materially, or through artifacts. A plan is a prospective representation generated or adopted under Sigma. A trace is a realization sampled from Sigma under particular states, observations, opportunities, disturbances, and outcomes. A policy is the pi component or, in broader formal usage, a subset of Sigma. A strategy instance is the activation of Sigma in a particular episode. # 9. Strategy Grammar and Composition A minimal grammar describes strategic organization without requiring one programming notation: STRATEGY ::= ORIENT ; ORGANIZE ; ENACT ; MONITOR ; {ADAPT \| RECOVER \| SWITCH}\* ; TERMINATE ORIENT ::= establish criteria \| classify situation \| estimate state \| identify constraints\ ORGANIZE ::= select policy \| construct plan \| choose heuristic \| allocate roles \| reserve resources\ ENACT ::= primitive action \| option \| procedure \| delegated action \| coordinated joint action\ MONITOR ::= observe outcome \| test assumption \| track criterion \| detect anomaly\ ADAPT ::= update parameter \| revise belief \| refine plan \| change abstraction\ RECOVER ::= undo \| compensate \| retry \| backtrack \| seek assistance \| replan\ SWITCH ::= replace policy \| invoke fallback \| change goal priority \| delegate\ TERMINATE ::= criterion met \| threshold reached \| resource exhausted \| infeasible \| abandoned Composition occurs through sequential composition, conditional branching, iteration, hierarchical invocation, parallel coordination, fallback, and arbitration. Composition is valid only when initiation conditions, resource assumptions, authority, and termination semantics are compatible. Strategy equivalence is typed. Two strategies may be outcome-equivalent but differ in risk, information use, opportunity dependence, trace distribution, recoverability, or transfer. No universal strategy-equivalence relation is justified. # 10. Strategy Lifecycle The lifecycle is recurrent rather than strictly linear. 1\. Formation: a strategy is generated, selected, learned, inherited, or socially assigned.\ 2. Adoption: the strategy becomes behaviorally controlling or commitment-bearing.\ 3. Initialization: state, criteria, opportunity, and resources are assessed.\ 4. Enactment: actions and information-gathering operations are selected.\ 5. Monitoring: outcomes, deviations, and uncertainty are evaluated.\ 6. Adaptation: parameters, beliefs, plans, or action rules change while strategy identity is retained.\ 7. Switching: a materially different organizing structure replaces or suspends the current one.\ 8. Recovery: the agent repairs consequences or returns to a viable state.\ 9. Termination: completion, abandonment, interruption, or supersession occurs.\ 10. Consolidation: experience updates skill, habit, memory, artifacts, or reusable strategy components.\ 11. Transfer: components are activated or transformed in a new context. Identity across adaptation requires declared invariants. A strategy may remain the same if its criterion structure, state abstraction, or high-level policy remains stable while parameters change. If the organizing rule or criteria change beyond the declared tolerance, the model should record a strategy switch rather than adaptation. # 11. Inferring Strategies Strategy inference is an abductive and model-comparison problem. It should not begin with labels assigned to visually similar traces. The inference protocol is: 1\. Declare the episode boundaries, observation model, and behavioral trace.\ 2. Specify the strategy-bearing system and level of attribution.\ 3. Enumerate feasible rival strategies before inspecting outcomes where possible.\ 4. For each candidate, state predicted action distributions, information requests, latency patterns, error responses, switching behavior, and outcome distributions across diagnostic contingencies.\ 5. Collect repeated or strategically informative episodes rather than relying on one successful sequence.\ 6. Use interventions that separate rivals: change information availability, action cost, risk, feedback, state structure, or opportunity.\ 7. Incorporate elicited plans and verbal reports as fallible evidence, not privileged access.\ 8. Fit candidate models with uncertainty and penalize unnecessary complexity.\ 9. Evaluate out-of-sample prediction, calibration, and counterfactual discrimination.\ 10. Report underdetermination where multiple candidates remain observationally equivalent. Strong strategy evidence comes from cross-context stability plus diagnostic adaptation. A candidate should predict not merely common actions but different responses under contingencies where rival strategies diverge. # 12. Strategy Evidence Hierarchy Level 0 - Raw record: timestamps, sensor values, commands, utterances, or system events. Level 1 - Verified behavioral event: a coded event supported by an explicit detection rule. Level 2 - Episode trace: ordered or partially ordered attributed events under declared boundaries. Level 3 - Descriptive regularity: recurrence, sequence motif, transition probability, or path distribution. Level 4 - Candidate strategic organization: a model connecting state, observation, criteria, and conditional selection. Level 5 - Rival discrimination: evidence that the candidate explains diagnostic contingencies better than specified alternatives. Level 6 - Transfer and adaptation evidence: the candidate predicts persistence, modification, or reuse across contexts. Level 7 - Causal support: intervention on a proposed strategy component changes behavior as predicted. Level 8 - Mechanistic or implementation support: independent evidence identifies the process or architecture implementing the strategy. Level 9 - Formal verification: for declared artificial systems, the implemented policy and switching structure are proven to satisfy specified properties. Claims must not skip levels. A repeated sequence supports a regularity, not by itself a strategy. A verbal description supports reported planning, not necessarily the generative organization of action. # 13. Comparative Cases Novice and expert. A novice may use serial visible search and local trial-and-error; an expert may use recognition, hidden commands, hierarchical chunks, and anticipatory recovery. Equal success does not imply equal strategy. Evidence must distinguish knowledge, motor fluency, opportunity belief, and state abstraction. Deterministic and adaptive policies. A deterministic scripted agent can instantiate a strategy when the script includes conditional organization across states. An adaptive policy may preserve strategy identity while updating parameters. Stochasticity does not negate strategy; randomness may implement exploration or robustness. Human and artificial agents. Artificial policies may be inspectable at implementation level, while human strategies usually remain inferred. Formal equivalence between a human model and an artificial policy does not imply psychological identity. Individual and collaborative strategies. Team strategy may reside in role allocation, communication protocol, shared artifacts, and mutual commitments rather than in any one participant. A distributed strategy can persist despite membership changes if coordination invariants remain stable. Situated improvisation. Locally improvised action can still be strategic when it preserves criteria through conditional organization. Suchman's critique rules out treating the plan as exhaustive cause, not the possibility of strategic structure. Interface migration. A user may preserve a high-level strategy while replacing low-level actions, or preserve a learned sequence while losing its effectiveness. Transfer should therefore be assessed component by component. # 14. Strategy, Transfer, and Learning Transfer is not proof of strategy identity. A source strategy may transfer intact, only a heuristic may transfer, or a procedure may be reused under an incompatible state abstraction. Positive performance transfer can occur through increased familiarity without preservation of the original strategy. Strategy transfer requires a correspondence between source and target components: criteria, state abstractions, opportunity structures, action repertoires, and contingency rules. The strongest evidence shows that a source-derived organizing rule predicts target behavior under diagnostic conditions better than alternatives. Strategy evolution can occur through parameter tuning, policy refinement, composition, decomposition, abstraction change, habit formation, externalization into tools, social redistribution, or replacement. Researchers should distinguish within-strategy adaptation from strategy switching using predeclared identity criteria. # 15. Falsification and Rival Accounts The framework should be narrowed or rejected under five conditions. Policy sufficiency: if a conventional policy mapping plus state representation and reward fully captures every relevant strategic distinction, the broader strategy contract is unnecessary. The present analysis finds that information policies, commitments, switching, recovery, resources, and distributed organization often require explicit treatment, but these could be incorporated into an augmented policy formalism. Trace sufficiency: if strategy labels add no predictive or explanatory gain beyond trace features and context, strategy should remain a descriptive category rather than a latent construct. Plan identity: if explicit plans consistently and exhaustively determine behavior across contingencies, situated revision components are unnecessary. Existing evidence strongly contradicts this universal claim. Inference unreliability: if independent analyses cannot recover comparable strategy attributions or if rival models remain observationally indistinguishable, claims must be restricted to descriptive regularities. No transfer or intervention gain: if inferred strategies do not predict adaptation, transfer, or responses to diagnostic interventions better than simpler models, strategy attribution lacks scientific value. # 16. Threats to Validity Strategy is a scale-relative concept. What appears strategic at one level may be a primitive action at another. Every analysis must declare temporal scale and unit of attribution. Human strategy inference is vulnerable to post hoc rationalization, observer bias, and flexible labeling. Artificial-agent strategy descriptions are vulnerable to anthropomorphism in the opposite direction: an optimized policy need not contain human-like goals, intentions, or reasoning. Outcome-based selection creates circularity when a "successful strategy" is defined by success and then used to explain it. Criteria and candidate structures should be specified independently of observed outcomes. Sparse observations may make different strategies observationally equivalent. Missing information about beliefs, opportunity, and external artifacts can misattribute distributed organization to the individual. Cultural, institutional, and collaborative strategies may not decompose cleanly into individual policies. The framework permits distributed attribution but does not solve every boundary problem. # 17. Implications for Interaction Research The strategy framework connects the prior theory stack without collapsing its layers. Interaction defines reciprocal or recurrent coupling. Behavior provides attributed trajectories. Measurement specifies how records support claims. Similarity supplies typed comparison. Transfer identifies source-dependent effects across contexts. Strategy explains conditional organization across actions and contingencies. For empirical research, strategy should be modeled only after opportunity and observation conditions are represented. An action absent from the believed opportunity set cannot be treated as deliberately rejected. A failed recovery sequence may reflect missing permission or inaccessible signaling rather than a poor strategy. For formal modeling, the strategy contract identifies requirements that a candidate formalism must support: partial observability, temporal abstraction, information action, resource limits, switching, recovery, composition, distributed control, and uncertainty over attribution. For design and evaluation, the framework discourages normative shortcuts. A strategy that is slower may be more robust, auditable, transferable, or accessible. Comparison must therefore remain criterion-relative and typed. # 18. Conclusion Existing theories are sufficient in their constituent concepts, but no single inherited term cleanly coordinates strategy across planning, reinforcement learning, human problem solving, situated action, robotics, and interaction research. The warranted synthesis is not a new psychological primitive. It is a strategy-analysis contract that treats strategy as an inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response. Strategies are supported by traces but are not traces; may include plans but are not identical with plans; may be represented as policies but often require information, commitment, switching, recovery, and resource structure; and may transfer only partially across contexts. Scientific strategy claims require rival models, diagnostic contingencies, explicit uncertainty, and evidence beyond successful action sequences. This framework supplies the bridge from behavior and transfer to the next phase of the research program: determining which formal models can represent interaction episodes, opportunity profiles, traces, strategies, composition, and uncertainty without losing the distinctions already established. # 19. Reusable Artifacts ## A. Strategy Ontology ----------------------------------------------------------------------- Element Definition ----------------------------------- ----------------------------------- Strategy-bearing system Individual, artificial agent, team, or distributed arrangement to which organization is attributed. Domain Declared class of interaction situations. State/observation Actual and accessible conditions relevant to selection. Opportunity profile Typed action availability and recoverability. Criteria Goals, constraints, values, risks, commitments, or thresholds. State abstraction Distinctions treated as decision-relevant. Action repertoire Primitive and temporally extended actions. Selection policy Conditional relation from represented conditions to action. Information policy Rules for observing, searching, testing, or querying. Commitment Conditions that stabilize prior choices. Contingency/recovery Rules for failure, uncertainty, and repair. Switch/stop rules Conditions for replacement, suspension, completion, or abandonment. Resources Time, attention, memory, computation, tools, authority, and collaborators. Evidence Records and tests supporting attribution. ----------------------------------------------------------------------- ## B. Strategy Taxonomy ----------------------------------------------------------------------- Dimension Types ----------------------------------- ----------------------------------- Control Open-loop; closed-loop; receding-horizon; event-triggered; mixed Representation Plan; procedure; policy; heuristic bundle; reactive controller; distributed pattern Uncertainty Certainty-equivalent; information-seeking; risk-sensitive; robust; exploratory; adaptive Selection Deterministic; stochastic; satisficing; optimizing; lexicographic; threshold; convention Revision Fixed; parameter-adaptive; structure-adaptive; opportunistic; reflective Social Individual; delegated; negotiated; role-based; jointly committed; distributed Learning Preconfigured; acquired; transferred; composed; imitated; self-discovered Evidence Hypothesized; supported; rival-discriminated; causally supported; verified ----------------------------------------------------------------------- ## C. Strategy Contract - Declared domain and attribution level - Episode boundaries and timescale - Criteria and constraints - State and observation model - State abstraction or belief model - Opportunity assumptions - Action and skill repertoire - Conditional selection policy - Information-acquisition policy - Commitment and persistence rules - Contingency and recovery rules - Switching and stopping conditions - Resource and authority assumptions - Expected outcomes and risks - Identity invariants under adaptation - Evidence and rival strategies - Uncertainty and validity domain ## D. Strategy Inference Protocol 1\. Declare episodes, traces, and observation model. 2\. Specify strategy bearer and temporal scale. 3\. Enumerate rival strategies. 4\. Derive diagnostic predictions for each candidate. 5\. Collect repeated and diagnostic episodes. 6\. Intervene on information, cost, risk, feedback, or opportunity. 7\. Treat reports and plans as fallible evidence. 8\. Fit models with uncertainty and complexity control. 9\. Evaluate held-out and counterfactual discrimination. 10\. Report underdetermination and prohibited interpretations. ## E. Strategy Evidence Hierarchy ----------------------------------------------------------------------- Level Evidence status ----------------------------------- ----------------------------------- 0 Raw record 1 Verified behavioral event 2 Episode trace 3 Descriptive regularity 4 Candidate strategic organization 5 Rival discrimination 6 Transfer/adaptation support 7 Causal intervention support 8 Mechanistic implementation support 9 Formal verification ----------------------------------------------------------------------- # 20. References Bratman, M. E. (1987). Intention, Plans, and Practical Reason. Harvard University Press. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Cohen, P. R., & Levesque, H. J. (1990). Intention is choice with commitment. Artificial Intelligence, 42(2-3), 213-261. Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451-482. Hutchins, E. (1995). Cognition in the Wild. MIT Press. Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101, 99-134. Newell, A., & Simon, H. A. (1972). Human Problem Solving. Prentice-Hall. Norman, D. A. (1986). Cognitive engineering. In D. A. Norman & S. W. Draper (Eds.), User Centered System Design. Erlbaum. Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99-118. Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. Sutton, R. S., Precup, D., & Singh, S. (1999). Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211. Bacon, P.-L., Harb, J., & Precup, D. (2017). The option-critic architecture. Proceedings of AAAI. Fikes, R. E., & Nilsson, N. J. (1971). STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2, 189-208. Rao, A. S., & Georgeff, M. P. (1995). BDI agents: From theory to practice. Proceedings of ICMAS. Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. Knowledge Engineering Review, 10(2), 115-152. ======================================================================== ## FILE: docs/02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.md (694 lines, 34.8 KiB) ======================================================================== **Formal Models of Computational Interaction** *Toward a Mathematical Foundation* Cross-disciplinary foundational research paper # Abstract This paper evaluates whether one established formalism can represent the interaction theory developed across prior work on ontology, semantics, representation, projection, opportunity, behavior, measurement, similarity, transfer, and strategy. Labeled transition systems, Petri nets, process algebras, statecharts, event structures, workflow nets, Markov decision processes, partially observable Markov decision processes, category-theoretic process models, and multi-agent formalisms are compared by a common set of obligations: bounded interaction episodes, reciprocal coupling, partial-order behavior, typed opportunity, projection and observation, latent strategy, uncertainty, empirical traces, composition, and typed equivalence. No candidate satisfies every obligation without extension. Labeled transition systems provide the smallest operational core and the broadest verification ecosystem, but interleaving semantics obscures true concurrency and standard forms omit observation, policy, measurement, and empirical uncertainty. Event structures preserve causality, conflict, and concurrency but are less convenient for state-rich, stochastic, and instrumented systems. Petri nets and workflow nets excel at concurrency, resources, and completion. Process algebras provide the strongest native composition and behavioral equivalence theory. MDPs and POMDPs provide decision, uncertainty, belief, and strategy semantics but ordinarily presuppose a fixed action/state model and weakly represent organizational and representational structure. Statecharts provide hierarchy and practical specification but lack one universally accepted mathematical semantics. Category theory supplies a principled language of composition and translation rather than a sufficient empirical model by itself. The evidence therefore supports a conservative hybrid foundation rather than a new calculus: an observation-enriched probabilistic labeled transition system as the canonical semantic kernel; event-structure or Petri-net views for concurrent causality and resource flow; process-algebraic operators for composition and equivalence; and POMDP-style belief and policy layers where agency under uncertainty is part of the explanandum. A trace-and-measurement morphism connects formal executions to empirical records. The paper supplies a formal ontology mapping, core semantics, model comparison matrix, expressiveness analysis, and recommended foundation. # 1. Problem Statement The established interaction theory imposes obligations that exceed ordinary interface-state modeling. An interaction episode has declared participants, boundary, timescale, coupling, preconditions, transitions, invariants, evidence, failure, recovery, and completion. Behavior is a bounded attributed trajectory under an observation model rather than raw telemetry. Opportunity distinguishes domain-valid, capable, permitted, enabled, reachable, exposed, signaled, believed, executable, successful, and reversible action. Strategy is a latent, temporally extended organization of conditional action selection. Measurement connects records to variables and claims through explicit operationalization and uncertainty. Similarity is typed rather than universal. A formal foundation must preserve these distinctions while remaining analyzable and compositional. The central problem is not which formalism is most expressive in the abstract. It is which minimal combination represents the established ontology without encoding every distinction as an informal annotation or inventing a new mathematical language. # 2. Evaluation Method Each candidate formalism was evaluated against the same representation obligations. The assessment distinguishes native expressiveness from expressibility by arbitrary encoding. A universal programming language can encode nearly any finite model, but such encodability does not make its semantics transparent or its analyses appropriate. The criteria were: (1) episode boundaries and identity; (2) state and transition semantics; (3) reciprocity and coupling; (4) concurrency and causal independence; (5) nondeterminism; (6) probability and uncertainty; (7) partial observability and projection; (8) opportunity and authorization; (9) policy and strategy; (10) empirical trace alignment; (11) composition and decomposition; (12) equivalence and refinement; (13) verification and quantitative analysis; and (14) suitability for estimation from observed interaction data. The review prioritized foundational sources: labeled transition systems and model checking; Murata on Petri nets; Milner on process algebra; Harel on statecharts; Winskel on event structures; workflow-net soundness; Sutton and Barto on MDPs; Kaelbling, Littman, and Cassandra on POMDPs; and categorical process semantics. The conclusion is comparative and architectural, not a claim that all systems should be implemented using one notation. # 3. Formal Obligations Derived from the Theory The formal object must distinguish six kinds of state: domain state, participant state, authority state, projection state, observer or belief state, and measurement state. Combining them into one Cartesian state is mathematically possible but destroys explanatory modularity and causes state-space explosion. The foundation should therefore permit factored state and typed transition labels. An interaction episode requires more than a transition path. It requires a boundary predicate, participant assignment, coupling relation, initiating and completion conditions, and evidence linking the modeled episode to observations. Reciprocal constraint need not mean simultaneous bidirectional transition. It can be represented by causal dependence across a bounded execution: an event of one participant changes the enabled, probable, observable, or valued future of another, whose subsequent event recurrently constrains the first or the shared system. Opportunity requires multiple predicates over actions and states rather than one action set. Projection and observation require mappings from domain states and transitions to exposed operations and observable symbols. Belief requires probability or possibility over hidden states. Strategy requires a policy-like object over histories, observations, or beliefs, plus temporally extended organization where needed. Empirical use requires a stochastic or uncertain observation channel from executions to records. # 4. Labeled Transition Systems A labeled transition system (LTS) consists minimally of states, action labels, and a transition relation. It provides the clearest common denominator for enabled actions, executions, traces, reachability, safety, liveness, refinement, simulation, and bisimulation. Interaction episodes can be represented as bounded executions satisfying initiation and completion predicates. Typed labels can identify actor, channel, operation, authorization result, and outcome. The principal strength of LTS semantics is analyzability. Model checking, equivalence checking, reachability, temporal logic, and compositional reductions are mature. LTSs also serve as semantic targets for statecharts, process algebras, workflow systems, and many programming languages. The limitations are equally important. Standard interleaving semantics represents concurrent events as alternative sequences and therefore loses causal independence unless enriched. Ordinary LTSs do not natively distinguish projection from domain state, observation from execution, permission from enablement, policy from transition availability, or empirical records from formal traces. Probability, time, cost, and partial observability require extensions. The LTS is therefore the best semantic kernel, not a complete interaction model. # 5. Petri Nets and Workflow Nets Petri nets represent distributed state through places and tokens and behavior through transition firing. They are particularly strong for concurrency, synchronization, resource consumption, conflict, invariants, boundedness, liveness, and reachability. Their graphical and algebraic structure makes them well suited to workflows, multi-party protocols, and interactions in which independent activities and shared resources matter. Workflow nets add distinguished source and sink conditions and support soundness questions concerning completion, residual tokens, and dead transitions. These concepts correspond naturally to interaction initiation, completion, deadlock, and cleanup. Standard place-transition nets remain weak for rich data, hierarchical projection, belief, policy, and measurement. Colored, timed, stochastic, and inhibitor-arc variants increase expressiveness but fragment analysis and can approach general programming-language complexity. Petri nets should therefore be treated as a concurrent-resource view of the canonical model, especially where partial-order structure and completion are central. # 6. Process Algebras Process algebras such as CCS, CSP, and the pi-calculus represent systems through processes and operators for action prefix, choice, parallel composition, synchronization, hiding, relabeling, and recursion. Their major contribution is not simply another transition notation; it is a compositional theory in which the behavior of a whole can be derived from interacting parts and compared through rigorously defined observational relations. This is highly aligned with the interaction theory. Participant processes can be composed through channels, internal actions can be hidden, projections can be modeled by abstraction or renaming, and typed equivalences can express what an observer can distinguish. Process algebra offers the strongest native account of compositional interaction identity and substitutability. Classic process algebras are less natural for quantitative human behavior, empirical traces, continuous variables, resources, belief, and learning. Probabilistic, timed, stochastic, and hybrid variants exist, but no single process calculus has become the universal cross-disciplinary foundation. Process algebra is best used to define composition, interface contracts, and equivalence over the transition kernel. # 7. Statecharts Statecharts extend state machines with hierarchy, orthogonality, and broadcast communication. These features address practical complexity: hierarchical states support abstraction; orthogonal regions represent concurrency; history supports resumption; and event-triggered transitions support reactive behavior. They are highly usable for engineered interactive systems and can align naturally with interface modes and lifecycle states. Their weakness as a foundational theory is semantic plurality. Variants differ in event queues, step semantics, priority, run-to-completion, concurrency, and history. Statecharts can be translated into transition systems, but the resulting semantics must be declared explicitly. They are therefore an effective authoring and presentation notation rather than the canonical mathematical substrate. # 8. Event Structures Event structures represent computations as event occurrences constrained by causality, consistency, enabling, and conflict. They distinguish true concurrency from mere nondeterministic interleaving and make partial-order traces primary. This is valuable for interaction because logs often impose a total order that is not causally justified, and because distributed or collaborative episodes contain independent events. Event structures also support counterfactual questions about which events depend on which prior events and which alternatives exclude one another. These relations are closer to the interaction paper's recurrent-constraint account than a flat sequence is. However, event structures are less direct for mutable data-rich state, continuous quantities, reward, partial observation, and online estimation. Probabilistic and game extensions exist, but tool ecosystems are narrower. Event structures should be available as a causal-concurrency semantics derived from or linked to the transition kernel. # 9. MDPs and POMDPs A Markov decision process represents states, actions, transition probabilities, rewards, and policies. It directly supports stochastic behavior, expected outcomes, controllability through action, and strategy evaluation. A partially observable MDP adds observations and belief states, making it especially relevant to the distinction between actual state, projection, observation, believed actions, and expected consequences. These formalisms are the strongest candidates for opportunity, strategy, adaptation, and prediction. A projection can be represented partly through the observation kernel and available action function; belief mediates action selection; options can represent temporally extended policies. Their standard assumptions create limits. The Markov property may require state augmentation. A single optimizing agent and scalar reward may misrepresent collaborative, institutional, or interpretive interaction. Authorization, signaling, semantics, and measurement validity are not intrinsic. POMDP observations are probabilistic signals, not the complete concept of representation or projection. MDP/POMDP semantics should therefore be an optional decision layer over the interaction kernel, not the universal ontology. # 10. Category-Theoretic Process Models Category theory provides objects, morphisms, composition, identity, products, monoidal structure, functors, and natural transformations. In process-oriented applications, objects can represent interfaces or systems and morphisms can represent processes. Symmetric monoidal categories support parallel composition and diagrammatic reasoning. Functors can relate different semantic models while preserving composition. This makes category theory valuable for expressing the architecture of the research program: multiple views of one interaction model, compositional contracts, translations between Petri nets and execution categories, and preservation claims across projections. It is particularly suited to stating when a translation is structure preserving. Category theory does not by itself choose the empirical entities, transition probabilities, observation model, or measurement semantics. Treating it as the primary model would move essential commitments into the choice of category. It should therefore serve as a meta-level compositional and translation framework, not the sole executable semantics. # 11. Multi-Agent and Game-Based Models Multi-agent systems represent multiple agents with local states, actions, observations, protocols, knowledge, goals, and sometimes utilities. Concurrent game structures add strategic choice and adversarial or cooperative outcomes. Epistemic and temporal logics can express what agents know and what coalitions can enforce. These models directly address distributed agency and asymmetric opportunity. They can represent authorization, imperfect information, joint action, coordination, negotiation, and strategic interaction better than single-agent MDPs. Their limitation is heterogeneity: multi-agent modeling is a family of frameworks rather than one semantics. Agent identity, rationality, knowledge, communication, and utility assumptions vary widely. The recommended foundation should permit multiple participant policies and local observation models without presupposing ideal rational agents or equilibrium behavior. # 12. Comparative Result No single candidate dominates across all obligations. LTSs lead on minimality, operational clarity, verification, and equivalence. Process algebras lead on native composition and observational substitutability. Event structures and Petri nets lead on true concurrency, causality, and resource flow. Statecharts lead on practical hierarchical specification. POMDPs lead on partial observability, belief, policy, and stochastic decision. Category theory leads on compositional translation across models. The comparison rejects two alternatives. A monolithic Cartesian-state POMDP can encode nearly every distinction but makes ontology, authority, representation, measurement, and composition opaque. A purely process-algebraic foundation captures interaction structure but leaves empirical uncertainty, belief, and data-model alignment as external additions. The minimal defensible solution is therefore a layered semantic profile with one canonical kernel and formally related views. # 13. Recommended Formal Foundation The recommended kernel is an observation-enriched probabilistic labeled transition system (OEPLTS): M = \. N is the set of participants and system components. S is a factored state space. A is a typed action/event vocabulary. T(s,a,s\') is a nondeterministic or probabilistic transition relation. I and F define episode initiation and completion. C defines effective capability. P defines authorization. X defines exposure through a projection. O maps hidden state and events to observer-accessible observations. Y maps executions to instrument records. R defines recovery or reversibility relations. A participant-relative strategy is a history-, observation-, or belief-dependent policy pi_i. Belief update is added when O is non-injective or stochastic. Rewards or criteria are optional and typed rather than mandatory. A coupling relation K identifies cross-component dependencies by which an event or state change of one component alters another component\'s enabled transitions, transition probabilities, observations, or value-relevant futures. The kernel has three associated semantics. Its unfolding into an event structure provides causal and concurrent semantics. Its composition through process-algebraic operators provides modular semantics and behavioral equivalences. Its decision enrichment into an MDP, POMDP, stochastic game, or decentralized POMDP provides policy and uncertainty semantics. Petri-net or workflow projections represent resource and completion structure. Category-theoretic functors can state preservation across these views. Empirical linkage is explicit: an execution omega generates an observation trace through O and an instrument record through Y. Segmentation and attribution functions turn records into behavioral events under a measurement contract. This prevents formal traces from being equated automatically with observed behavior. # 14. Formal Semantics An execution is a finite or infinite alternating sequence s0, a0, s1, a1, \... satisfying T. An interaction episode is an execution segment bounded by I and F in which the declared coupling criterion K is satisfied. Reciprocity is tested over the causal dependency graph, not merely by the presence of actions from multiple actors. The executable set for participant i at state s is the intersection of domain-valid, capable, permitted, and enabled actions. Exposure and signaling are additional projection-relative predicates and need not coincide with executability. Believed availability is defined over the participant\'s belief state and may include false positives or omit executable actions. Composition is defined by synchronized product over shared labels or explicit channels, with hiding and relabeling. Independent transitions may interleave operationally but are retained as concurrent in the event-structure unfolding. Refinement is typed: trace inclusion, simulation, bisimulation, probabilistic bisimulation, testing equivalence, opportunity preservation, or measurement-relative equivalence must be selected explicitly. The model is implementation independent. A GUI, CLI, API, conversational agent, robot, or collaborative workflow is represented through different projection, observation, and action mappings over a declared domain and transition semantics. # 15. Analyzability and Empirical Suitability The recommended kernel preserves access to mature algorithms: reachability, invariant checking, temporal-logic model checking, simulation and bisimulation checking, probabilistic model checking, controller synthesis, policy evaluation, and partial-order reduction. Factored state and modular composition are necessary to reduce state explosion. Empirical suitability requires a different set of checks. Model states and labels must be operationally linked to records; hidden variables must not be treated as observed; timing and missingness must be represented; and parameter estimates must carry uncertainty. Conformance between traces and models should distinguish deviation, observation error, abstraction error, and model misspecification. The formal model is therefore not itself a measurement instrument. It is a theory-constrained representation whose empirical use depends on a measurement contract, estimation procedure, and validation evidence. # 16. Falsification and Threats to Validity The recommendation should be rejected or narrowed if a single established formalism can represent all required distinctions natively, preserve modularity, support the necessary analyses, and connect to empirical records without ad hoc layers. It should also be rejected if the proposed mappings cannot be made semantics-preserving or if independent analysts cannot reproduce the ontology-to-model mapping. A second threat is over-formalization. Human interaction boundaries, intentions, semantics, and social rules may be contested or emergent. Formal precision does not eliminate uncertainty about what should be modeled. A third threat is state explosion and undecidability: increased expressiveness can destroy analyzability. A fourth is false realism: a model can be internally coherent while omitting institutional, environmental, or representational variables that generated observed behavior. The foundation therefore makes scope conditions explicit. It is strongest for computationally mediated episodes with declared operations, participants, records, and boundaries. Open-ended cultural activity may require qualitative and historical explanation alongside formal modeling. # 17. Conclusion The minimum adequate foundation is not a new universal calculus. It is a conservative layered architecture centered on an observation-enriched probabilistic labeled transition system. The LTS kernel supplies state, transition, execution, reachability, and verification. Process algebra supplies composition and typed behavioral equivalence. Event structures or Petri nets supply concurrency, causality, and resource flow. POMDP or game enrichments supply partial observation, belief, policy, and stochastic strategy. Measurement mappings connect executions to records and claims. Category theory can organize translations and preservation across these views. This recommendation preserves the strongest existing mathematics while matching the conceptual distinctions already established. It also leaves open an empirical test: if the layered model does not improve specification, comparison, explanation, verification, or prediction relative to simpler baselines, the additional structure should be removed. # 18. Reusable Artifacts ## A. Formal Ontology Mapping ----------------------------------------------------------------------- Concept Formal interpretation ----------------------------------- ----------------------------------- Interaction episode Bounded execution segment satisfying initiation, completion, and coupling predicates. Participant Typed component or agent with local state, actions, and observation access. Domain state Facts determining transition semantics independent of presentation. Projection state Representation and access-path configuration exposed to a participant. Authority state Roles, permissions, and policy conditions. Observation Participant-accessible symbol or signal generated from hidden state/event. Instrument record Timestamped or structured record emitted by the measurement channel. Action/event Typed occurrence capable of participating in a transition. Transition Possible or probabilistic state change labeled by an event. Coupling Cross-component dependency that changes possible or probable future trajectories. Opportunity profile Typed predicates over validity, capability, permission, enablement, exposure, belief, reachability, and recovery. Strategy/policy History-, observation-, or belief-dependent organization of action selection. Execution A path or partial-order configuration licensed by the model. Behavioral trace Attributed event structure derived from records under an observation and measurement contract. Equivalence Declared preservation relation over selected observables and transformations. ----------------------------------------------------------------------- ## B. Model Comparison Matrix ---------------------------------------------------------------------------------------------------------------------------- Formalism Native strengths Uncertainty Composition Empirical fit Equivalence Recommended role ------------------ ------------------ ------------- ------------- ------------------ ------------- ------------------------- LTS State, Weak without Strong Strong Moderate Kernel transitions, extension reachability, traces, temporal properties Petri net Concurrency, Moderate via Moderate Strong for process Moderate Concurrent/resource view synchronization, stochastic logs resources, variants invariants Process algebra Composition, Moderate via Very strong Moderate Strong Composition/equivalence communication, variants layer hiding, equivalence Statechart Hierarchy, Weak to Moderate Strong for Moderate Authoring notation orthogonality, moderate engineering models reactive lifecycle Event structure Causality, Moderate via Strong Moderate Strong Causal-concurrency view conflict, true extensions concurrency Workflow net Completion, Moderate Moderate Very strong Moderate Workflow specialization workflow soundness, process flow MDP Stochastic Strong Moderate Strong with data Moderate Decision enrichment transitions, rewards, policies POMDP Observation, Very strong Moderate Strong but Moderate Epistemic/strategy belief, policy estimation-heavy enrichment under uncertainty Category theory Composition and Depends on Very strong Weak alone Abstractly Meta-level architecture translations chosen strong between models category Multi-agent/game Local observation, Strong in Moderate Moderate Strong for Participant enrichment joint action, stochastic strategic strategic ability variants equivalence ---------------------------------------------------------------------------------------------------------------------------- ## C. Expressiveness Mapping ----------------------------------------------------------------------- Required construct Recommended representation ----------------------------------- ----------------------------------- Episode boundaries Predicates I and F over execution states/events Reciprocal coupling Dependency relation K over components, transitions, observations, or enabled sets Concurrency Event-structure unfolding or Petri-net projection; partial-order reduction Opportunity Typed state/action predicates C, P, E, X plus reachability and recovery Projection State-dependent mapping from domain model to exposed actions and observations Measurement Channel Y from execution to records plus segmentation/attribution functions Uncertainty Probabilistic transition and observation kernels; interval or imprecise variants where needed Strategy Policies over histories, observations, or beliefs; options for temporal extension Composition Synchronized product, parallel operator, hiding, relabeling, interface contracts Similarity/equivalence Trace, simulation, bisimulation, testing, probabilistic, opportunity, and measurement-relative relations ----------------------------------------------------------------------- ## D. Recommended Formal Profile Canonical kernel: observation-enriched probabilistic labeled transition system. Composition semantics: process-algebraic synchronized product, hiding, relabeling, recursion, and typed equivalence. Concurrency semantics: event-structure unfolding or Petri-net projection when causal independence and resources matter. Decision semantics: MDP, POMDP, stochastic-game, or decentralized enrichment only when uncertainty, policy, or strategic choice is part of the explanatory target. Empirical semantics: observation channel and instrument-record channel governed by the Measurement Contract and Behavioral Evidence Contract. Translation semantics: explicit structure-preserving mappings between views, optionally formalized as functors. # 19. References Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking. MIT Press. Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-580. Milner, R. (1980). A Calculus of Communicating Systems. Springer. Milner, R. (1989). Communication and Concurrency. Prentice Hall. Hoare, C. A. R. (1985). Communicating Sequential Processes. Prentice Hall. Harel, D. (1987). Statecharts: A visual formalism for complex systems. Science of Computer Programming, 8, 231-274. Winskel, G. (1987). Event structures. In Advances in Petri Nets 1986, LNCS 255. Springer. van der Aalst, W. M. P. (1998). The application of Petri nets to workflow management. Journal of Circuits, Systems and Computers, 8(1), 21-66. van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action. Springer. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101, 99-134. Fagin, R., Halpern, J. Y., Moses, Y., & Vardi, M. Y. (1995). Reasoning About Knowledge. MIT Press. Alur, R., Henzinger, T. A., & Kupferman, O. (2002). Alternating-time temporal logic. Journal of the ACM, 49(5), 672-713. Baez, J. C., & Stay, M. (2010). Physics, topology, logic and computation: A Rosetta Stone. In New Structures for Physics. Springer. Baez, J. C., Genovese, F., Master, J., & Shulman, M. (2021). Categories of nets. arXiv:2101.04238. van Glabbeek, R. J. (1990). The linear time-branching time spectrum. CONCUR 1990. Springer. Park, D. (1981). Concurrency and automata on infinite sequences. Theoretical Computer Science. Clarke, E. M., Grumberg, O., & Peled, D. A. (1999). Model Checking. MIT Press. Cassandras, C. G., & Lafortune, S. (2008). Introduction to Discrete Event Systems (2nd ed.). Springer. Reisig, W. (2013). Understanding Petri Nets. Springer. ======================================================================== ## FILE: docs/02_Research_Papers/13_Formal_Models/The_Limits_of_Computational_Interaction_Models_v0.2.md (238 lines, 6.7 KiB) ======================================================================== # The Limits of Computational Interaction Models **Version:** Draft 0.2 **Project:** Foundations of Computational Interaction **Status:** Foundational Position Paper --- # Abstract Every scientific framework is defined not only by what it explains, but by what it refuses to claim. This document establishes the epistemic boundaries for Foundations of Computational Interaction. It argues that interaction models should seek structure without determinism, formalization without false certainty, generality without reductionism, and integration without replacing adjacent disciplines. The purpose of these limits is not to weaken the discipline. It is to make its claims scientifically defensible. --- # 1. Why Boundaries Matter New disciplines often fail by overextending their explanatory authority. If Foundations of Computational Interaction attempts to explain culture, cognition, personality, intelligence, organizations, and society through interaction alone, it will become another grand unified theory with little empirical value. Instead, the discipline should explicitly define where its authority begins and ends. Interaction models explain interaction. They do not explain people in their entirety. --- # 2. Culture Does Not Determine Behavior Culture shapes exposure, meaning, expectations, conventions, symbolism, and interaction practices. It does not determine behavior. The preferred model is: ```text Cultural and community context ↓ changes probabilities of exposure, meaning, expectation, and practice ↓ interacts with individual history, task, representation, and situation ↓ contributes to behavior ``` Research should therefore investigate mechanisms rather than treating demographic identity as causal. --- # 3. Interaction History Does Not Fully Explain Individuals Accumulated interaction experience may improve explanation beyond demographic categories, but it is only one explanatory layer. Behavior also depends upon: - current objectives; - domain knowledge; - accessibility; - fatigue; - immediate context; - consequences; - uncertainty; - individual variation. Interaction Ecology should therefore remain probabilistic rather than deterministic. ```text Behavior = interaction history × task × representation × opportunity × immediate state × individual variation ``` --- # 4. Interaction May Not Reduce to a Fixed Grammar A canonical interaction grammar is valuable only if it preserves explanatory power. Interaction may instead require a layered grammar. ```text Input Form ↓ Semantic Action ↓ Situated Action ↓ Activity ``` The discipline should determine whether interaction possesses a finite primitive grammar, an extensible grammar, or no stable grammar at all. --- # 5. Internal Cognition Cannot Be Directly Observed Interaction systems observe behavior. They do not observe beliefs, confidence, curiosity, understanding, trust, or intention directly. Those remain latent constructs. Every inference should preserve the distinction: ```text Observed Behavior ↓ Behavioral Feature ↓ Candidate Interpretation ↓ Uncertainty ``` Behavior must never be silently promoted into psychology. --- # 6. Representation Is Not the Only Cause of Behavior Representation influences interaction. It does not fully explain it. Behavior emerges through multiple interacting factors. ```text Behavior = semantic state × representation × morphology × interaction grammar × opportunity structure × agent state × task ``` Representation should therefore be studied as one manipulated variable rather than the sole explanatory mechanism. --- # 7. Formalization Does Not Eliminate Ambiguity Ontologies, formal models, and computational systems improve reproducibility. They do not eliminate ambiguity. Formalization moves ambiguity into: - construct definitions; - event classification; - opportunity boundaries; - model assumptions; - interpretation rules. The contribution of formalization is not certainty. Its contribution is inspectable uncertainty. --- # 8. One Ontology Should Not Replace Existing Disciplines Foundations of Computational Interaction should integrate findings across: - Human–Computer Interaction; - Psychology; - Anthropology; - Human Factors; - Design; - Information Science. It should not replace them. The ontology provides a shared relational structure through which findings become comparable. --- # 9. Similarity Is Not a Universal Score Interaction comparison is always relative to a target, frame, correspondence mapping, observables, admissible transformations, metrics, tolerances, uncertainty, and validity domain. Semantic similarity does not establish opportunity, behavioral, strategy, causal, or measurement similarity. When a defensible common comparison space cannot be established, the result is incomparability rather than a forced ranking. # 10. A Trace Does Not Reveal a Strategy Strategies are latent explanatory constructs. A repeated sequence supports a descriptive regularity, not by itself a plan, policy, intention, habit, or strategy. Scientific strategy attribution requires rival models, diagnostic contingencies, uncertainty, repeated evidence, and preferably intervention or out-of-sample discrimination. # 11. A Metric Is Not a Construct A numerical measure does not become comprehension, confidence, expertise, trust, quality, or accessibility merely by being renamed. Every measurement claim must declare its measurand, observation process, operationalization, scale, uncertainty, validity evidence, population, task, projection, and permitted interpretation. # 12. Contracts Do Not Eliminate Judgment Projection, Opportunity, Interaction, Behavioral Evidence, Measurement, Similarity, and Strategy Contracts make assumptions inspectable. They do not eliminate boundary choices, coding judgment, model selection, interpretation, or uncertainty. # 13. A Doctrine of Bounded Explanation Foundations of Computational Interaction should adopt the following doctrine: - Seek structure without determinism. - Seek formalization without false certainty. - Seek generality without reductionism. - Seek integration without disciplinary replacement. - Preserve uncertainty rather than concealing it. - Distinguish observation from interpretation. - Prefer mechanisms over categories. These principles define the epistemic limits of the discipline. --- # 14. Conclusion The long-term credibility of Foundations of Computational Interaction will depend as much on the claims it refuses to make as the claims it advances. A disciplined ontology should clarify what interaction models can explain, what they may only suggest, and what remains outside their authority. Those boundaries are not weaknesses. They are prerequisites for scientific rigor. ======================================================================== ## FILE: docs/02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.md (1083 lines, 51.1 KiB) ======================================================================== **Predicting Interaction** *Toward a Predictive Theory of Computational Interaction* Formal research paper # Abstract Computational interaction is predictively tractable only under declared targets, horizons, observation models, populations, interventions, and loss functions. Existing research supplies successful local predictive laws and models: Fitts\' law predicts constrained movement time; Hick-Hyman relations predict choice latency under controlled alternatives; GOMS and the Model Human Processor predict skilled task time; cognitive architectures generate task-specific performance trajectories; Bayesian, survival, sequential, and machine-learning models forecast events under uncertainty. These successes do not establish a universal predictive theory. Discovery, errors, recovery, abandonment, adaptation, expertise, transfer, and strategy differ in observability, temporal scale, causal dependence, and distributional stability. Prediction must therefore be typed. This paper distinguishes forecasting from explanation, retrodiction, diagnosis, causal effect estimation, and intervention planning. It proposes a prediction ontology and a layered framework in which predictions are conditional distributions over declared interaction targets generated from episode state, opportunity structure, projection, behavioral history, agent experience, strategy hypotheses, and context. Predictive claims must report calibration, discrimination, decision utility, uncertainty, transport conditions, and failure criteria. The central conclusion is that computational interaction supports predictive science, but only as a family of scoped, probabilistic, and updateable models. Low-level performance and near-term transitions are often strongly predictable; higher-order constructs and long-horizon outcomes are forecastable only as distributions and frequently remain unidentified without intervention or richer observation. # 1. Problem Statement The preceding research program defines interaction episodes, behavioral traces, opportunity profiles, strategies, transfer, similarity, and a measurement architecture. Prediction is the next test of whether these constructs support empirical science rather than only conceptual organization. The relevant question is not whether some interaction outcomes correlate with earlier variables. It is whether future or unobserved interaction variables can be forecast with known uncertainty under declared conditions and whether the resulting forecasts remain valid across participants, tasks, projections, time, and interventions. Interaction is an especially difficult predictive domain. The system and agent mutually constrain later trajectories; observations are partial; behavior changes beliefs and opportunity; participants learn; interfaces and policies change; and the prediction itself may alter behavior. Prediction targets also occupy different levels. A movement time is directly measurable, while a strategy, expertise state, or believed action set is latent. A model can predict a trace without explaining its mechanism, explain a mechanism without predicting held-out traces, or estimate an intervention effect without accurately predicting individual outcomes. The central research problem is therefore to define a disciplined predictive architecture that separates target types, horizons, information sets, causal questions, uncertainty, and validity domains. The objective is not one universal model. It is the minimum framework required to state, test, compare, update, and falsify predictive claims about computational interaction. # 2. Literature Review Method The review was organized by predictive function rather than by discipline. Primary and foundational sources were prioritized for: statistical distinctions between explanation and prediction; human-performance laws; engineering models of skilled interaction; cognitive architectures; Bayesian and sequential models; machine learning; survival and event-history analysis; causal inference; transfer and transport; and predictive uncertainty. The earlier Interaction, Behavior, Measurement, Opportunity, Similarity, Transfer, Strategy, and Formal Models papers were treated as constraints on the predictive target and evidence model, not as evidence that prediction must succeed. Each tradition was evaluated against five questions: What is predicted? From what information? At what horizon and unit? Under what assumptions? By what evidence is success or failure established? Claims were rejected as predictive when they were evaluated only in-sample, used future information, relied on post-outcome labels, lacked a baseline, or did not report uncertainty and calibration. # 3. Explanation, Prediction, and Intervention Prediction and explanation are distinct scientific aims. Predictive modeling minimizes expected loss for unobserved cases under a specified data-generating regime. Explanatory modeling aims to identify or support mechanisms, causes, or theoretical dependencies. A structurally faithful explanatory model can predict poorly when unmodeled variability dominates, while a flexible predictor can forecast accurately without identifying the generating mechanism. This distinction is emphasized by Shmueli and by Yarkoni and Westfall. Four additional functions must remain separate: - Retrodiction estimates an unobserved or hidden past variable from later evidence. - Diagnosis classifies or explains a current condition from observations. - Causal effect estimation predicts the distribution that would follow an intervention rather than passive observation. - Decision or control selects an intervention using predicted consequences and utilities. Observational prediction estimates P(Y_future \| H_observed). Intervention prediction estimates P(Y_future \| do(A=a), H_observed). The latter cannot generally be obtained from the former without causal assumptions, identification conditions, or experimental variation. A system that accurately predicts abandonment from frustration signals does not thereby establish that reducing those signals will prevent abandonment. # 4. Prediction Ontology ----------------------------------------------------------------------- **Concept** **Definition** **Example** ----------------------- ----------------------- ----------------------- Prediction target The future, hidden, or Discovery event, error, counterfactual variable completion time, to be forecast. strategy class. Prediction unit Entity over which the Action, episode, prediction is defined. person-task pair, team, system deployment. Horizon Temporal or structural Next action; remainder distance between of episode; next information cutoff and session. target. Information set Variables legally State, projection, available at prediction opportunity, prior time. trace, experience. Predictor Function or Hazard model, POMDP probabilistic model belief model, neural mapping information to sequence model. a predictive distribution. Predictive distribution Uncertainty-bearing Probability of error; estimate over outcomes. interval for completion time. Decision threshold Rule converting a Intervene when failure distribution into an probability exceeds action or label. 0.7. Loss or utility Cost function defining Log loss, time error, predictive quality for false-negative cost. a use. Validity domain Population, task, Trained novices on projection, context, desktop form and time for which completion. evidence supports use. Transport condition Assumption under which Stable measurement, performance generalizes mechanism, or to a target domain. conditional distribution. Calibration Agreement between Among 0.8 predictions, predicted probabilities about 80% occur. and observed frequencies. Discrimination Ability to rank or AUC, concordance, separate outcomes. precision-recall. Sharpness Concentration of a Narrow intervals with calibrated predictive valid coverage. distribution. Prediction failure Violation of accuracy, Drift, subgroup calibration, coverage, failure, intervention utility, or scope. mismatch. ----------------------------------------------------------------------- # 5. What Is Predictable? Predictability is not a property of a phenomenon alone. It is a relation among target, horizon, information set, population, observation process, model class, and tolerance. The same outcome may be highly predictable at the population level and weakly predictable for an individual. Aggregate movement time may follow a stable law while a particular person\'s next action remains uncertain. ---------------------------------------------------------------------------------- **Target** **Expected **Suitable models** **Principal predictability** limits** ------------------ -------------------- ----------------------- ------------------ Low-level Often high under Fitts-type movement Device motor/perceptual controlled geometry, time; Hick-Hyman choice variability, performance practiced action, latency. strategy changes, and stable devices. fatigue, accessibility, nonstationarity. Skilled procedural Moderate to high for KLM/GOMS and Model Learning, task time routine, error-free, Human Processor. interruptions, well-specified errors, tasks. interpretation, collaborative work. Next action or Moderate when state, Sequence models, Hidden goals, transition opportunity, policy, Markov/POMDP models. multiple valid and recent history strategies, are observed. changing opportunity. Discovery Probabilistic and Hazard of first Unobserved prior context-sensitive. discovery from knowledge and exposure, signaling, attention. search history. Errors Useful risk Human reliability, Rare events, prediction possible; classification, adaptive exact event state-space risk avoidance, prediction limited. models. reporting bias. Recovery Predictable Competing-risk or Unobserved conditional on error sequential models. interpretation and type, visible external recovery paths, consequences. belief, and skill. Abandonment Often forecastable Survival analysis using Censoring, return as a time-to-event friction and progress behavior, changing risk. signals. goals. Adaptation Predictable as a Bayesian learning, Task change, distribution over power-law/exponential exploration, learning curves or learning models. motivation, policy changes. strategy shifts. Expertise Population-level Skill models, cognitive Domain specificity classification is architectures, and sparse possible; individual longitudinal models. longitudinal data. developmental trajectory is weakly identified. Transfer Conditional and Hierarchical or Negative transfer, asymmetrical; transport models. representation requires mismatch, context source-target dependence. relation. Strategy Latent; only Inverse planning, Observational probabilistic mixture models, inverse equivalence and inference from reinforcement learning. strategy multiple traces and switching. interventions is defensible. Long-horizon Generally low Scenario distributions, Compounding interaction without closed-world policy-conditioned uncertainty, trajectory assumptions and simulation. exogenous change, continual updating. reflexivity. ---------------------------------------------------------------------------------- # 6. Predictive Traditions ## 6.1 Human-performance laws Fitts\' law and Hick-Hyman relations demonstrate that constrained components of interaction can support compact, quantitative prediction. Their scientific value comes from declared task structure, measurable variables, reproducible relations, and explicit residual variation. Their limitation is scope: they predict selected performance dimensions under particular action and choice structures, not whole interactions. ## 6.2 Engineering models of interaction GOMS, the Keystroke-Level Model, and the Model Human Processor predict skilled, largely error-free task performance from decomposed operators and processing assumptions. They are strongest when methods and operators are known and weakest when discovery, learning, interpretation, collaboration, interruption, or strategy change dominates. ## 6.3 Cognitive architectures ACT-R, EPIC, and related architectures generate predictions by instantiating mechanistic assumptions about memory, perception, cognition, and action. They can explain and predict within modeled tasks, but performance depends on task encoding, model construction, parameter selection, and whether the architecture captures the relevant environmental coupling. Architecture-level commitments do not remove the need for out-of-sample validation. ## 6.4 Bayesian and sequential models Bayesian models express uncertainty over states, parameters, hypotheses, and future observations. State-space models, hidden Markov models, MDPs, and POMDPs are natural for interaction because they distinguish latent state, observation, action, transition, and belief. They become predictive only after the transition and observation models are estimated or constrained, and their validity depends on stationarity and state sufficiency. ## 6.5 Machine learning Machine learning expands predictive capacity through flexible representation and regularized out-of-sample optimization. It is appropriate for heterogeneous traces, nonlinear interactions, and high-dimensional histories. It does not automatically provide causal interpretation, transportability, or calibrated uncertainty. Strong performance within a random split may conceal failure across users, tasks, time, systems, or interventions. ## 6.6 Survival, reliability, and event-history models Discovery, failure, recovery, and abandonment are naturally represented as time-to-event or competing-risk problems. These models handle censoring and changing hazards more appropriately than binary labels. Recurrent-event and multi-state variants can represent repeated errors, recovery cycles, and episode transitions. # 7. Candidate Predictive Framework Let an interaction episode be represented by the layered formal model established previously. For participant x at time t, define the legally available predictive information: H_t = \ where s_t is system state; pi_t is projection; O_t is typed opportunity structure; Q_t is authority and policy state; y_0:t is the recorded and attributed trace up to the cutoff; e_x is measured experience; b_t is a belief-state estimate where justified; z_t is a strategy hypothesis distribution; and c_t is declared context. For target Y at horizon h under prediction regime r, the predictor produces: p(Y\_{t+h} \| H_t, r, M, D) where M identifies model assumptions and D identifies the training or calibration evidence. Under an intervention a, the target becomes p(Y\_{t+h} \| do(a), H_t, M, D). The two expressions must not be substituted without identification assumptions. The predictive framework contains six linked layers: - Target layer: target, unit, horizon, outcome definition, competing outcomes, and censoring. - Information layer: cutoff, observable variables, derived variables, latent estimates, and prohibited future information. - Model layer: predictor family, priors or regularization, update rule, and causal assumptions. - Uncertainty layer: aleatoric, epistemic, measurement, distributional, and structural uncertainty. - Evaluation layer: baselines, held-out design, calibration, discrimination, interval coverage, and utility. - Validity layer: population, task, projection, time, intervention, and monitoring conditions. # 8. Causal Assumptions Predictive accuracy does not establish a causal mechanism. Causal claims require an explicit causal graph or structural model, temporal ordering, intervention semantics, and assumptions concerning confounding, selection, measurement, and interference. Four distinctions are mandatory: - Prediction under observation versus prediction under intervention. - Individual treatment or intervention response versus average effect. - Mediation as a causal claim versus predictive feature contribution. - Transport across contexts versus ordinary cross-validation within one context. The interaction domain intensifies interference: one participant\'s action changes the state and opportunities of others; system adaptations alter later observations; and predictive interventions may change the target process. Static independent-and-identically-distributed assumptions are therefore often inappropriate. Sequential causal models, randomized interventions, natural experiments, or explicit policy evaluation are required for intervention claims. ----------------------------------------------------------------------- **Claim type** **Target** **Required **Example** assumptions** ----------------- ----------------- ----------------- ----------------- Associational Future outcome Temporal Will the current forecast under the ordering; stable episode end in observed regime. conditional abandonment? distribution. Causal effect Outcome Identification, Would adding a distribution consistency, recovery under an exchangeability signifier reduce intervention. or randomized failure? design. Policy value Expected utility Sequential When should help of an adaptive ignorability or be offered? intervention experimental policy. policy data; positivity. Mechanism Intermediate Correct Will belief prediction states generated structural update precede by a theory. specification and selection? measurable mediators. Transported Outcome in a new Declared Will a model prediction population or invariant trained on GUI projection. mechanisms or sessions work for reweighting voice? assumptions. ----------------------------------------------------------------------- # 9. Uncertainty and Prediction Limits A prediction should be a distribution, interval, set, ranked list, or hazard unless deterministic structure is independently established. Point predictions conceal uncertainty and invite false precision. The framework distinguishes: - Aleatoric uncertainty: irreducible variation conditional on the model and information set. - Epistemic uncertainty: uncertainty about parameters, functions, or hypotheses due to limited evidence. - Measurement uncertainty: error introduced by instruments, segmentation, coding, and construct operationalization. - State uncertainty: partial observability of current system, agent, or social state. - Structural uncertainty: uncertainty over causal structure, model family, or latent-state representation. - Distributional uncertainty: uncertainty caused by population, task, projection, policy, or temporal shift. - Reflexive uncertainty: change caused by revealing or acting on a prediction. Conformal prediction can provide finite-sample marginal coverage under exchangeability, but it does not solve conditional validity, causal transport, or nonstationary sequential interaction. Bayesian credible intervals depend on model and prior assumptions. Ensembles estimate some forms of model uncertainty but do not guarantee coverage. Uncertainty claims must therefore name the guarantee and its assumptions. Fundamental limits arise from observational equivalence, hidden goals, underdetermined strategies, partial observability, chaotic or highly sensitive dynamics, changing policies, endogenous learning, rare outcomes, insufficient support for interventions, and open-world exogenous events. In such cases the scientifically correct prediction may be a broad set, a ranked scenario distribution, or a declaration of non-identifiability. # 10. Target-Specific Analysis ## 10.1 Discovery Discovery should be predicted as a time-to-first-event process relative to an opportunity contract. Predictors may include exposure, signaling, search path, prior experience, modality, task state, and prior failed attempts. Unselected available actions cannot be labeled undiscovered without an independent awareness measure. Competing events include successful discovery, prompted discovery, alternate-path completion, and abandonment. ## 10.2 Opportunity System-relative feasible, permitted, enabled, and exposed sets are often computable rather than statistically predicted when the model is complete. Agent-relative believed actions and expected consequences require probabilistic estimation. Predictions should distinguish changes in actual opportunity from changes in belief or signaling. ## 10.3 Errors Error prediction should define the normative or task criterion, error opportunity, and exposure time. Rare-event evaluation requires precision-recall, calibrated risk, and cost-sensitive metrics rather than accuracy alone. Error labels must not collapse execution failure, goal mismatch, policy denial, misunderstanding, and system fault. ## 10.4 Recovery Recovery prediction is conditional on an initiating disruption and the available recovery graph. Suitable targets include time to repair, selected recovery path, probability of escalation, and residual consequence. Believed reversibility and actual reversibility must remain separate. ## 10.5 Abandonment Abandonment is a censored event, not merely absence of completion. Models should distinguish temporary pause, session termination, task substitution, and permanent non-return. Survival models with time-varying covariates are preferable when the hazard changes with progress and friction. ## 10.6 Adaptation Adaptation prediction concerns change in policy, belief, skill, or performance as experience accumulates. Learning curves forecast aggregate change but can conceal strategy shifts. Hierarchical state-space models can represent individual variation and update online. ## 10.7 Expertise Expertise is multidimensional and domain-relative. Prediction may classify current skill or forecast performance under familiar tasks, but long-term expertise development requires longitudinal exposure, practice quality, feedback, motivation, and domain structure. Demographic variables should not stand in for measured experience. ## 10.8 Transfer Transfer prediction requires a source-target similarity contract and a carrier hypothesis. Predictions should estimate positive, null, or negative source effects and uncertainty. Ordinary similarity or source performance alone is insufficient. ## 10.9 Strategy Strategy is latent and typically non-identifiable from one trace. Predictive inference should return a posterior over strategy hypotheses or next-action distributions, test alternative models, and update when contingencies reveal discriminating behavior. A model that predicts actions well may still misidentify strategy. # 11. Prediction Protocol ----------------------------------------------------------------------- **Step** **Requirement** ----------------------------------- ----------------------------------- 1\. Declare target Define the outcome, unit, horizon, event time, censoring, and competing outcomes. 2\. Freeze information cutoff List every variable available at prediction time; prohibit future-derived features. 3\. State use Separate scientific forecasting, diagnosis, causal intervention, control, and operational triage. 4\. Specify population and context Declare users or agents, task, projection, device, authority, environment, and time period. 5\. Register baselines Include prevalence, persistence, simple rules, human judgment, and established task models. 6\. Select evaluation design Use temporal, participant, task, projection, or deployment holdout appropriate to the intended claim. 7\. Fit without leakage Keep preprocessing, feature selection, imputation, and tuning within training folds. 8\. Quantify uncertainty Produce calibrated probabilities, intervals, sets, or hazards with named guarantees. 9\. Evaluate multiple properties Report discrimination, calibration, coverage, sharpness, utility, subgroup and context performance. 10\. Test transport Evaluate across time, participants, tasks, projections, systems, and policies when those claims are intended. 11\. Test interventions separately Use experiments or identified causal models for claims about changing outcomes. 12\. Monitor and update Detect drift, recalibrate, revise the validity domain, and document model changes. 13\. State failure conditions Define minimum acceptable gain, calibration, coverage, and decision utility before use. 14\. Preserve evidence lineage Link each prediction to the interaction, behavior, and measurement contracts that generated its inputs. ----------------------------------------------------------------------- # 12. Evaluation and Falsification A predictive theory of interaction should be rejected or narrowed if its constructs provide no reproducible out-of-sample gain over simpler baselines, if uncertainty is systematically miscalibrated, or if performance collapses under the contexts included in its claimed validity domain. ------------------------------------------------------------------------ **Claim** **Test** **Falsifying or narrowing evidence** ------------------------ ----------------------- ----------------------- P1 Scoped predictability Declared interaction Repeated external tests targets can be show no meaningful predicted above gain. preregistered baselines. P2 Typed advantage Opportunity, trace, Simpler state and transfer, and strategy history features match variables improve or outperform them. target-specific predictions when relevant. P3 Uncertainty validity Prediction intervals or Persistent probabilities are undercoverage or calibrated within probability declared scope. miscalibration. P4 Transport Specified invariant Performance degrades structures support beyond tolerance under prediction across planned shifts. declared contexts. P5 Intervention Observational and Observed association separation interventional reliably equals predictions differ intervention effect where confounding or under tested feedback exists. conditions, narrowing the distinction. P6 Predictive ranking and Across broad tests, the Prediction-explanation mechanistic adequacy best explanatory model distinction can diverge. always dominates prediction, contrary to current evidence. P7 Strategy uncertainty Multiple strategies Discriminating evidence remain plausible under reliably identifies one observationally strategy from the equivalent traces. available trace alone. P8 Updateability Sequential updating Static models remain improves calibration equally valid across under learning and declared drift. nonstationarity. ------------------------------------------------------------------------ Evaluation must include out-of-sample prediction. In-sample fit, significance, explained variance, and post hoc reconstruction do not suffice. For probabilistic classification, report proper scoring rules and calibration in addition to threshold metrics. For time-to-event prediction, report time-dependent discrimination, calibration, and censoring-aware scores. For sequences, report next-event and multi-step performance with horizon-specific degradation. For decisions, report expected utility and harm under the operational threshold. # 13. Threats to Validity - Target leakage can enter through post-outcome fields, retrospective labels, or segmentation choices informed by the full trace. - Random train-test splits can overstate generalization when the intended use concerns new people, tasks, projections, or future periods. - Construct labels such as confusion, expertise, and strategy may be unreliable or circular. - Adaptive systems violate stationarity because predictions and interventions change later data. - Rare failures can produce misleading accuracy and unstable subgroup estimates. - Models may encode historical access, training, or policy inequalities and treat them as stable individual propensities. - Predictive success can invite unwarranted causal and psychological interpretation. - Closed-world simulations may omit exogenous events that dominate deployed interaction. - Aggregate calibration can coexist with severe conditional or subgroup miscalibration. - A benchmark can become part of the design process, causing overfitting to the evaluation regime. # 14. Implications for Computational Interaction Science Prediction provides a stronger test of the research program than conceptual coherence alone. The established constructs should earn their place by improving forecast quality, uncertainty, transport, or intervention design relative to simpler state-and-trace models. Typed opportunity variables should help predict discovery and invalid attempts; transfer variables should improve target-context forecasts; strategy distributions should improve contingent action prediction; and formal interaction models should constrain impossible transitions and support simulation. Predictive success would not by itself establish an independent discipline. Many fields develop predictive models of interaction. A discipline-level claim would require cumulative laws or mechanisms, stable validity domains, shared benchmarks, transportable models, and explanatory or intervention gains that are not adequately supplied by existing HCI, human factors, psychology, machine learning, control, or systems theory. The immediate empirical program should therefore prioritize preregistered, multi-context forecasting studies with frozen contracts and strong baselines. The decisive evidence is incremental, held-out performance and calibration---not the apparent completeness of the ontology. # 15. Conclusion Computational interaction supports predictive scientific theories, but only in a scoped and plural sense. There is no evidence for universal prediction of whole interactions or individual behavior. Strong prediction is achievable for constrained motor and choice processes, routine skilled performance, and near-term transitions when the task, state, opportunity, and method are specified. Discovery, errors, recovery, and abandonment are predictively tractable as probabilistic event processes. Adaptation, expertise, transfer, and strategy can be forecast only through richer longitudinal and latent-state models, and their individual trajectories remain substantially uncertain. The warranted contribution is a predictive architecture rather than a new predictive primitive. It separates prediction from explanation and intervention; defines target, horizon, information, uncertainty, and validity; and requires held-out evaluation, calibration, transport tests, and explicit failure conditions. Interaction becomes predictively scientific when forecasts are reproducible, uncertainty-bearing, and bounded by declared contracts. Where those conditions cannot be met, the correct result is not a confident point estimate but a broad distribution, an incomparable context, or a statement that the target is not identified. # Reusable Artifacts ## A. Prediction Contract ----------------------------------------------------------------------- **Field** **Required declaration** ----------------------------------- ----------------------------------- Identity Prediction identifier, version, date, owner, intended scientific or operational use. Target Outcome, unit, level, horizon, event definition, censoring, competing events. Information cutoff Timestamp or episode boundary beyond which no input may be used. Inputs Observed records, derived variables, latent estimates, provenance, measurement uncertainty. Interaction scope Participants, episode boundaries, system state, projection, opportunity, policy, context. Model Family, parameters, priors, regularization, training procedure, update rule. Causal status Associational, interventional, transported, mechanism-based, or policy-value claim. Prediction form Probability, distribution, interval, set, hazard, sequence, ranking, or scenario. Uncertainty Aleatoric, epistemic, measurement, state, structural, distributional, reflexive. Evaluation Baselines, holdout design, metrics, calibration, coverage, utility, subgroup tests. Validity domain Population, task, projection, modality, system, policy, environment, time. Transport conditions Assumptions and evidence required for use outside the evaluation domain. Failure conditions Minimum gain, maximum error, calibration tolerance, abstention rule, stop-use conditions. Monitoring Drift tests, recalibration schedule, update triggers, audit trail. ----------------------------------------------------------------------- ## B. Prediction Evidence Hierarchy ----------------------------------------------------------------------- **Level** **Evidence type** **Meaning** ----------------------- ----------------------- ----------------------- 0 Raw record Timestamp, event payload, sensor sample. 1 Verified observation Quality-controlled event or state measurement. 2 Derived predictor Latency, path length, opportunity-set difference. 3 Latent estimate Belief, strategy posterior, expertise score. 4 In-sample association Fit within data used to construct the model. 5 Internal held-out Performance on held-out prediction units from the same regime. 6 Temporal or group Prediction for future generalization periods or unseen participants. 7 Cross-context transport Prediction across tasks, projections, devices, or systems. 8 Interventional Forecast under a prediction deliberately changed condition. 9 Replicated predictive Independent regularity replications with stable scope and uncertainty. ----------------------------------------------------------------------- ## C. Predictive Metric Registry ---------------------------------------------------------------------------- **Target form** **Metrics** **Interpretation** **Example** ----------------- ------------------ -------------------- ------------------ Continuous MAE/RMSE Magnitude error; Completion time, outcome RMSE emphasizes search time. large errors. Probabilistic Log loss/Brier Proper scoring of Error or binary score probability abandonment forecasts. probability. Ranking ROC-AUC/PR-AUC Discrimination; Risk ranking. PR-AUC preferred for rare positives. Calibration Calibration Agreement of All probabilistic slope/intercept, probabilities and targets. ECE, reliability frequencies. curve Intervals/sets Coverage and Validity and Time interval or width/set size sharpness. action-set prediction. Survival C-index, Censoring-aware Discovery, integrated Brier event prediction. recovery, score, time abandonment. calibration Sequence Cross-entropy, Next-event and Action sequence. edit distance, trajectory horizon accuracy prediction. Decision Expected utility, Value under an Adaptive help. net benefit, intervention regret threshold or policy. Transport Performance delta Stability across GUI to voice; and recalibration declared domains. novice to expert. need Abstention Risk-coverage Quality when model High-uncertainty curve may decline to episodes. predict. ---------------------------------------------------------------------------- ## D. Uncertainty Model ----------------------------------------------------------------------- **Type** **Definition** **Required treatment** ----------------------- ----------------------- ----------------------- Aleatoric Outcome variability Predictive remaining under the distribution; information set. irreducible risk. Epistemic Limited evidence about Posterior, ensemble, model or parameters. bootstrap; decreases with relevant data. Measurement Instrument, coding, Propagate from segmentation, construct measurement contract. error. State Hidden or partially Belief state or observed current filtering distribution. conditions. Structural Competing models or Model averaging or causal graphs. sensitivity analysis. Distributional Shift in population, Domain tests, drift task, projection, monitoring, robust policy, or time. sets. Reflexive Prediction or Policy-aware evaluation intervention changes and experimentation. behavior. ----------------------------------------------------------------------- ## E. Prediction Protocol Checklist 1\. Declare target: Define the outcome, unit, horizon, event time, censoring, and competing outcomes. 2\. Freeze information cutoff: List every variable available at prediction time; prohibit future-derived features. 3\. State use: Separate scientific forecasting, diagnosis, causal intervention, control, and operational triage. 4\. Specify population and context: Declare users or agents, task, projection, device, authority, environment, and time period. 5\. Register baselines: Include prevalence, persistence, simple rules, human judgment, and established task models. 6\. Select evaluation design: Use temporal, participant, task, projection, or deployment holdout appropriate to the intended claim. 7\. Fit without leakage: Keep preprocessing, feature selection, imputation, and tuning within training folds. 8\. Quantify uncertainty: Produce calibrated probabilities, intervals, sets, or hazards with named guarantees. 9\. Evaluate multiple properties: Report discrimination, calibration, coverage, sharpness, utility, subgroup and context performance. 10\. Test transport: Evaluate across time, participants, tasks, projections, systems, and policies when those claims are intended. 11\. Test interventions separately: Use experiments or identified causal models for claims about changing outcomes. 12\. Monitor and update: Detect drift, recalibrate, revise the validity domain, and document model changes. 13\. State failure conditions: Define minimum acceptable gain, calibration, coverage, and decision utility before use. 14\. Preserve evidence lineage: Link each prediction to the interaction, behavior, and measurement contracts that generated its inputs. ## F. Open Problems - Predictive identification of strategies under observational equivalence. - Calibrated individual prediction under sparse, nonstationary histories. - Transport across projections that preserve semantics but alter opportunity and measurement. - Prediction under adaptive interfaces where the model changes the data-generating process. - Causal prediction of assistance, explanation, and recovery interventions. - Joint uncertainty propagation from raw records through latent constructs to outcomes. - Benchmarks that preserve interaction boundaries and prevent target leakage. - Evaluation of whether the program\'s typed constructs add out-of-domain predictive gain. # References Anderson, J. R. (2007). How Can the Human Mind Occur in the Physical Universe? Oxford University Press. Angelopoulos, A. N., & Bates, S. (2021). A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification. arXiv:2107.07511. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Card, S. K. (1986). The Model Human Processor: A Model for Making Engineering Calculations of Human Performance. Proceedings of the Human Factors Society. Fitts, P. M. (1954). The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement. Journal of Experimental Psychology, 47(6), 381-391. Hick, W. E. (1952). On the Rate of Gain of Information. Quarterly Journal of Experimental Psychology, 4(1), 11-26. Hyman, R. (1953). Stimulus Information as a Determinant of Reaction Time. Journal of Experimental Psychology, 45(3), 188-196. Jastrzembski, T. S., & Charness, N. (2007). The Model Human Processor and the Older Adult: Parameter Estimation and Validation Within a Mobile Phone Task. Journal of Experimental Psychology: Applied, 13(4), 224-248. Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and Acting in Partially Observable Stochastic Domains. Artificial Intelligence, 101, 99-134. Lei, J., G\'Sell, M., Rinaldo, A., Tibshirani, R. J., & Wasserman, L. (2018). Distribution-Free Predictive Inference for Regression. Journal of the American Statistical Association, 113(523), 1094-1111. Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. Pearl, J. (2012). The Do-Calculus Revisited. Proceedings of UAI. Shmueli, G. (2010). To Explain or to Predict? Statistical Science, 25(3), 289-310. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. Yarkoni, T., & Westfall, J. (2017). Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning. Perspectives on Psychological Science, 12(6), 1100-1122. Earlier papers in the Computational Interaction research program: Interaction; Behavior; Measurement; Representation, Invariance, and Projection; Opportunity, Affordance, and Action Availability; Interaction Similarity; Interaction Transfer; Interaction Strategies; Formal Models of Computational Interaction. ======================================================================== ## FILE: docs/02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.md (923 lines, 43.3 KiB) ======================================================================== **Comparative Interaction** *Toward a Scientific Method for Comparing Computational Interactions* Formal research paper # Abstract Comparisons of computational interactions are commonly reduced to task time, error rate, preference, usability scores, feature counts, or interface-level judgments. Such comparisons are scientifically incomplete because they often fail to establish that the interactions share a target, task, population, boundary, observation model, or admissible comparison relation. They also collapse distinct dimensions - semantics, interaction structure, opportunity, behavior, strategy, accessibility, discoverability, recovery, cost, learning, and measurement quality - into a single ranking. This paper develops a cross-disciplinary method for comparing computational interactions independently of implementation. It integrates formal equivalence, process conformance, measurement theory, human factors, accessibility, multi-criteria analysis, and the preceding interaction-research framework. The central result is a gate-and-profile architecture. A comparison must first pass admissibility gates establishing declared targets, correspondence mappings, scope conditions, measurement comparability, and uncertainty. It then produces a typed comparison profile rather than an unqualified score. Aggregation is permitted only when a decision purpose, weighting rule, compensation assumptions, uncertainty treatment, and stakeholder authority are declared. The paper concludes that computational interactions can be compared scientifically, but not by a universal metric. Scientific comparison requires a comparison contract, typed evidence, dimension-specific measures, explicit invariants, and rules for equivalence, dominance, trade-off, and incomparability. The reusable artifacts are a comparison ontology, taxonomy, contract, protocol, evaluation framework, scorecard, admissible-comparison rules, and falsification matrix. # 1. Problem Statement A computational interaction is not identical to its implementation, interface, trace, outcome, or user judgment. The same computational target may be projected through a graphical interface, command language, API, conversational system, or assistive modality. These projections may preserve operation semantics while changing exposed actions, signaling, path length, error recovery, auditability, motor demands, learning requirements, and strategy. A scientific comparison must therefore answer two questions in order. First: are the candidate interactions comparable under a declared frame? Second: on which dimensions are they equivalent, different, better, worse, or incomparable? Most evaluation practice begins with the second question and leaves the first implicit. The primary contribution of this paper is a method that separates comparison admissibility from comparative judgment. The method prevents three recurring errors: comparing unlike targets as though they were variants of one interaction; treating a metric as a complete construct; and converting multidimensional differences into a total ranking without an explicit decision model. # 2. Foundations Inherited from the Research Program The method inherits six constraints. Representation theory establishes that a projection selectively preserves, transforms, omits, and introduces properties. Opportunity theory separates possible, permitted, reachable, exposed, signaled, believed, selected, executed, successful, and reversible action relations. Interaction theory requires declared participants, boundaries, coupling, timescale, events, transitions, and completion. Behavior theory treats traces as evidence generated under an observation model rather than as transparent behavior. Measurement theory requires a declared measurand, operationalization, scale, uncertainty, validity domain, and permissible interpretation. Interaction-similarity theory distinguishes token identity, type identity, typed equivalence, graded similarity, and incomparability. These constraints jointly imply that comparison is not a single function applied to two interfaces. It is an argument supported by mappings, measurements, and scope conditions. # 3. Literature Foundations ## 3.1 Formal equivalence and conformance Formal methods compare systems relative to observables and abstraction rules. Trace equivalence, simulation, bisimulation, testing equivalence, refinement, and observational equivalence preserve different properties. Process mining similarly separates fitness, precision, generalization, and simplicity when comparing event logs and process models. Alignment-based conformance identifies correspondences and deviations rather than assuming event-token identity. These traditions support a central rule: comparison relations must be typed before they are computed. Conformance is not the same as superiority. A trace may conform closely to a model while imposing high human cost; a model may permit desired behavior while also permitting unsafe or irrelevant behavior. Formal relations therefore constrain comparison but do not exhaust it. ## 3.2 Measurement and context of use Measurement theory requires stable representational relations, permissible transformations, and uncertainty statements. Metrological traceability concerns the documented chain linking results to references. In interaction research, the relevant chain links records to detected events, attributed behavior, derived variables, constructs, and claims. ISO 9241-11 defines usability relative to specified users, goals, and contexts of use, with effectiveness, efficiency, and satisfaction as outcomes. This supports context-indexed comparison rather than universal interface quality. A result for one population, task, device, or environment does not automatically transport to another. ## 3.3 Accessibility and non-compensatory requirements Accessibility standards show why some dimensions cannot be averaged away. WCAG separates perceivability, operability, understandability, and robustness into testable success criteria. Failure of keyboard access or text alternatives cannot be scientifically neutralized by faster performance for another population. Accessibility therefore motivates threshold, veto, and subgroup-preservation rules rather than purely compensatory scoring. ## 3.4 Multi-criteria decision analysis Multi-criteria decision analysis distinguishes description from preference aggregation. Weighted sums assume commensurability and compensation: a deficit on one criterion can be offset by strength on another. Outranking methods permit partial orders and incomparability when evidence, thresholds, or stakeholder priorities do not justify a total ranking. Comparative interaction should adopt this discipline. A scientific profile describes differences; a decision model may rank alternatives, but the ranking is conditional on declared values and constraints. # 4. Comparison Ontology ----------------------------------------------------------------------- **Concept** **Definition** ----------------------------------- ----------------------------------- Comparison object The interaction token, type, projection, trace distribution, opportunity profile, strategy, or system pair being compared. Reference frame The declared target, task, population, context, boundary, timescale, and observation model. Correspondence mapping A mapping between entities, states, operations, events, outcomes, or measurements across candidates. Invariant A property required to remain unchanged for the comparison claim. Dimension A typed aspect of comparison such as semantic, structural, opportunity, behavioral, accessibility, or cost. Measure An operational rule producing evidence about a dimension. Tolerance A declared interval or threshold within which differences count as equivalent or acceptable. Uncertainty Incomplete knowledge attached to records, mappings, estimates, model assumptions, or transport. Admissible transformation A change allowed without invalidating the comparison, such as renaming, modality substitution, or temporal rescaling. Veto condition A non-compensatory failure that blocks equivalence, dominance, or deployment under the declared purpose. Comparison result A typed relation: identical, equivalent, similar, dominant, trade-off, or incomparable. Decision rule An optional value-laden rule for ranking or selecting candidates from the scientific profile. ----------------------------------------------------------------------- # 5. Interaction Comparison Taxonomy ----------------------------------------------------------------------- **Dimension** **Comparison question** **Primary evidence** ----------------------- ----------------------- ----------------------- Semantic preservation Whether operations, Formal specification, state meanings, model mapping, expert constraints, and validation. outcome interpretations correspond. Interaction Whether participant Interaction Contracts; preservation roles, coupling, protocol and transition protocol, boundaries, analysis. transitions, and completion conditions correspond. Opportunity Whether feasible, Opportunity matrices, preservation permitted, reachable, discovery studies, exposed, signaled, authorization analysis. believed, and recoverable actions correspond. Behavioral preservation Whether attributed Trace alignment, event and episode sequence models, distributions distributional tests. correspond under compatible observation models. Strategy preservation Whether inferred Multi-task evidence, conditional perturbation tests, organization, strategy models. information use, switching, and recovery policies correspond. Accessibility Whether relevant Standards conformance populations can plus user evidence. perceive, operate, understand, and robustly use the interaction. Discoverability Whether operations and Unaided discovery, relations can be found time-to-discovery, cue under declared prior recognition. knowledge and search conditions. Reversibility and Whether consequences Recovery graph, repair recovery can be undone, success, residual harm repaired, compensated, and cost. or safely explored. Interaction cost Resources consumed Time, actions, motor during performance. distance, attention, memory, energy, money, risk. Learning cost Resources and exposure Learning curves, required to achieve a trials-to-criterion, declared criterion. retention and transfer. Measurement quality Whether evidence is Measurement contracts, valid, reliable, invariance tests, comparable, traceable, uncertainty budgets. and uncertainty-bounded. ----------------------------------------------------------------------- # 6. Admissibility Gates A comparison should not proceed directly to metrics. It must pass the following gates. Failure does not imply that the candidates cannot be discussed; it means the proposed scientific comparison is unsupported or must be narrowed. ----------------------------------------------------------------------- **Gate** **Question** **Required **Typical evidence** failure** ----------------- ----------------- ----------------- ----------------- G1 Target Is the underlying Target Different goals target, function, definitions; are treated as or declared semantic variants of one purpose correspondence task. sufficiently map. aligned? G2 Boundary Are participants, Interaction One candidate episode Contracts. includes setup or boundaries, recovery while timescales, the other initial excludes it. conditions, and completion rules aligned? G3 Opportunity Are differences Opportunity Interface in permissions, Contracts. differences are capabilities, credited for backend backend functions, and capability reachable differences. outcomes identified? G4 Observation Do records, event Behavioral Different logging detection, Evidence coverage is segmentation, Contracts. interpreted as attribution, and behavioral missingness difference. permit comparison? G5 Measurement Are constructs, Measurement Scores from scales, Contracts; non-equivalent instruments, invariance and instruments are populations, and reliability directly uncertainty evidence. compared. compatible? G6 Correspondence Can entities, Mapping table Labels are actions, events, with ambiguous assumed to outcomes, and and unmapped identify costs be elements. equivalent defensibly operations. mapped? G7 Ethics and Are safety, Veto rules; Average gains accessibility rights, subgroup conceal a blocked exclusion, and analysis; or harmed accessibility standards subgroup. constraints evidence. represented? ----------------------------------------------------------------------- # 7. Comparison Relations After admissibility, a result should use one of six relations rather than the undifferentiated term "better." ----------------------------------------------------------------------- **Relation** **Meaning** **Evidence** ----------------------- ----------------------- ----------------------- Token identity The same historically Stable identity and bounded episode or provenance. record lineage. Typed equivalence All required invariants Equivalence tests or fall within declared formal proof. tolerances for a named dimension. Similarity A graded relation under Distance, distribution, a declared metric and or model-based estimate comparison frame. with uncertainty. Dominance One candidate is no Comparable dimensions worse on all mandatory and directionality. dimensions and better on at least one. Trade-off Candidates differ in Profile plus optional opposing directions and stakeholder decision no value-neutral model. ordering follows. Incomparability No defensible common Documented gate failure frame, mapping, or unresolved measurement, or uncertainty. preference relation exists. ----------------------------------------------------------------------- # 8. Comparative Evaluation Framework The recommended evaluation output has three layers. Layer 1 - invariants and vetoes. These establish semantic target, safety, authority, accessibility minima, and other non-negotiable constraints. A candidate failing a veto is not equivalent or admissible for the declared use, regardless of aggregate performance. Layer 2 - typed profile. Each dimension is reported with operational definition, estimate, uncertainty, evidence quality, and relevant subgroup or context. This is the scientific result. Layer 3 - optional decision synthesis. Ranking or selection may use dominance, lexicographic rules, constrained optimization, utility functions, or outranking. The decision rule must be separated from the scientific profile and must disclose weights, thresholds, compensation assumptions, and authority to set them. # 9. Interaction Scorecard ----------------------------------------------------------------------- **Domain** **Indicators** **Result form** **Required note** ----------------- ----------------- ----------------- ----------------- Target and Operation and Pass / partial / Formal mapping; semantics outcome fail unresolved preservation mismatches Interaction Roles, coupling, Profile Structural and structure protocol, temporal completion deviations Opportunity Executable, Profile False-positive exposed, and hidden signaled, opportunity rates believed, recoverable sets Behavior Trace and outcome Profile Compatible distributions segmentation and uncertainty required Strategy Conditional Profile / latent Requires organization and convergent recovery evidence across contingencies Accessibility Perceivable, Threshold + Report by operable, profile relevant access understandable, needs robust Discoverability Unaided discovery Profile Separate exposure and signaling from belief effectiveness Reversibility Undo, repair, Threshold + Irreversible compensation, profile harms are veto residual effects candidates Performance cost Time, action, Profile No universal motor, cognitive, common unit financial, risk Learning cost Exposure, Profile Separate instruction, familiarity and trials, transfer retention, transfer Measurement Validity, Quality grade Low quality quality reliability, constrains all invariance, downstream claims missingness, uncertainty ----------------------------------------------------------------------- # 10. Comparison Protocol - 1\. State the decision-independent scientific question and identify the candidate interactions. - 2\. Declare target semantics, task, users or agents, context, initial-state distribution, episode boundary, timescale, and success conditions. - 3\. Instantiate an Interaction Contract, Opportunity Contract, Behavioral Evidence Contract, and Measurement Contract for each candidate. - 4\. Construct correspondence mappings for entities, states, operations, events, outcomes, strategies, and measures. Mark one-to-many, ambiguous, and unmapped elements. - 5\. Declare invariants, admissible transformations, equivalence tolerances, mandatory thresholds, and veto conditions before examining comparative outcomes. - 6\. Test admissibility gates. Narrow the claim or declare incomparability where gates fail. - 7\. Select dimension-specific measures and justify their scales, directionality, uncertainty, and subgroup relevance. - 8\. Collect or derive evidence using compatible observation and attribution rules. Preserve raw records and provenance. - 9\. Estimate typed differences with uncertainty. Use equivalence tests for sameness claims and superiority tests only for directional claims. - 10\. Report the multidimensional profile, including null, conflicting, and subgroup-specific results. - 11\. Apply an optional decision rule only after the profile is complete. Conduct weight, threshold, and uncertainty sensitivity analysis. - 12\. State validity domain, transport limits, unresolved mappings, alternative explanations, and falsifying evidence. # 11. Admissible Comparison Rules - No comparison without a declared comparison object and reference frame. - No claim of semantic preservation from equal task completion alone. - No claim of behavioral preservation from identical aggregate outcomes alone. - No comparison of traces without compatible observation, segmentation, and attribution models. - No inference of strategy identity from one trace or one successful sequence. - No aggregation across dimensions without a declared decision purpose and compensation rule. - No averaging across populations when a mandatory subgroup threshold is relevant. - No accessibility credit from technical conformance alone when actual operability is disputed; standards and user evidence play different roles. - No cost comparison without declaring included resources, excluded externalities, and time horizon. - No equivalence claim without tolerances and adequate precision to support them. - No ranking when uncertainty intervals, missing mappings, or value conflicts support only a partial order. - Implementation independence permits different realizations, not the omission of implementation-mediated constraints that alter actual interaction. # 12. Comparative Cases ## 12.1 GUI and command line over the same operation set A GUI and CLI may preserve backend operations and outcomes while differing in exposure, signaling, composition, auditability, motor demands, memory demands, and learning cost. Semantic equivalence can coexist with opportunity and behavioral inequivalence. Experts may obtain lower execution cost from the CLI while novices achieve higher discovery from the GUI. The result is typically a trade-off profile, not a universal winner. ## 12.2 API and conversational interface An API may expose a precisely typed operation set with explicit errors, while a conversational interface paraphrases capabilities and may over-signal unsupported actions. Equal successful outcomes on benchmark tasks do not establish equivalent permission transparency, predictability, recovery, or auditability. Unsupported conversational claims create false-positive believed opportunities and should be represented as a veto or severe mismatch where consequential actions are involved. ## 12.3 Accessibility variants Visual, auditory, tactile, and multimodal projections may preserve target semantics while changing sequence, latency, spatial comparability, memory burden, error detection, and recovery. Comparison requires population- and assistive-technology-specific evidence. Aggregate performance across users can conceal exclusion. The correct output is a subgroup-indexed accessibility and opportunity profile. ## 12.4 Novice and expert use The implementation and exposed operations may be identical while believed actions, strategy, search, confidence, and recovery differ. This is not an interface-only comparison. The reference frame must include prior experience, and learning cost should be compared through longitudinal or transfer-sensitive designs rather than single-session performance alone. ## 12.5 Simulated and observed interaction A simulation may match transition frequencies or task outcomes yet fail to preserve causal mechanisms, adaptation, social coordination, or measurement processes. Model-to-observation comparison must separately report calibration, trace conformance, causal adequacy, and transport. Simulation should not be treated as a substitute population without validation. # 13. Statistical and Formal Analysis Claims of equivalence should use equivalence or non-inferiority designs with prespecified smallest effects of interest, not failure to reject a difference. Repeated measures, hierarchical populations, learning, and task heterogeneity require multilevel models. Time-to-discovery and abandonment are event-time outcomes; errors and recovery are often recurrent events; traces may require sequence alignment, process conformance, or probabilistic model comparison. Multiple dimensions create multiplicity and selective-reporting risks. Confirmatory dimensions should be preregistered. Exploratory profiles should remain labeled as exploratory. Missingness is often informative: an unobserved action may reflect logging limits, access barriers, or abandonment. Uncertainty should propagate from record detection and correspondence mappings through construct estimates and final comparisons. Formal equivalence can establish strong guarantees within an abstraction, but empirical claims require validating that the abstraction preserves the phenomena of interest. Conversely, empirical similarity does not establish formal equivalence or causal identity. # 14. Decision Synthesis without Conceptual Collapse A scorecard may support decisions, but a universal interaction score is rejected. Aggregation is appropriate only when criteria are commensurable or a defensible value function is supplied. Weighted sums permit compensation and can hide threshold failures. Lexicographic rules prioritize one criterion before others. Constrained optimization maximizes selected objectives subject to non-negotiable limits. Outranking supports partial orders where one candidate is sufficiently strong on important criteria without being vetoed by severe weaknesses. Sensitivity analysis is mandatory. A decision is robust only if reasonable variation in weights, thresholds, measurement uncertainty, and population assumptions does not reverse it. When rankings are unstable, the correct result is conditional preference or incomparability, not false precision. # 15. Falsification Matrix ------------------------------------------------------------------------- **Claim challenged** **Falsifying evidence** **Consequence** ----------------------- ------------------------- ----------------------- Typed profiles add no A validated scalar Replace the profile value measure predicts all with that measure relevant outcomes and within its proven decisions across systems, domain. populations, tasks, and contexts without hidden trade-offs. Admissibility gates are Comparisons remain valid Remove unsupported unnecessary when targets, boundaries, gates. observation models, or mappings differ materially. Implementation Every meaningful Narrow the framework to independence is comparison depends implementation classes. incoherent irreducibly on implementation-specific details. Opportunity comparison Semantic and behavioral Remove opportunity as a is redundant measures fully explain separate dimension. exposure, belief, permission, and recovery differences. Strategy comparison is No protocol distinguishes Treat strategy as unidentifiable strategy from trace exploratory only. variation or task response with acceptable reliability. Accessibility can be Empirical and normative Remove veto treatment fully compensatory evidence supports for that domain. averaging access failures against gains elsewhere for the declared use. Comparison contracts do Independent teams using Revise or reject the not improve the contract do not contract. reproducibility converge more than teams using ordinary reports. Profiles cannot support Decision makers cannot Reduce the framework to decisions use typed profiles more descriptive science. reliably than existing evaluations. ------------------------------------------------------------------------- # 16. Threats to Validity The framework is broad and may appear to solve comparison by requiring extensive declarations. Its value therefore depends on demonstrating improved reproducibility, error detection, and decision quality relative to simpler evaluation reports. Some comparisons will remain underdetermined because goals, values, or correspondence mappings are contested. This is not necessarily methodological failure; incomparability may be the scientifically correct result. Construct proliferation is another risk. The taxonomy should be reduced when dimensions are empirically redundant under a declared domain. Conversely, low correlations do not automatically prove conceptual independence because instruments may be unreliable or contexts heterogeneous. The framework also risks privileging interactions with enumerable tasks and state spaces. Open-ended creative, social, and institutional interactions may require interpretive or qualitative comparisons alongside formal and quantitative evidence. Such evidence remains admissible when its observation, coding, reflexivity, and inference rules are explicit. Finally, implementation independence has limits. Rendering latency, hardware, modality, network behavior, and device constraints can alter coupling, opportunity, and cost. The theory compares interactions independently of any particular implementation language or product, but it cannot discard implementation properties that causally alter the phenomenon. # 17. Conclusion Computational interactions can be compared scientifically when comparison is treated as a structured evidential argument rather than a feature checklist or universal score. The minimum method is a gate-and-profile architecture. First, admissibility gates establish a shared target, boundary, opportunity structure, observation model, measurement system, correspondence mapping, and ethical or accessibility constraints. Second, a typed profile compares semantic preservation, interaction structure, opportunity, behavior, strategy, accessibility, discoverability, reversibility, performance cost, learning cost, and measurement quality. Third, an optional decision model may aggregate or rank only after its values, thresholds, compensation assumptions, and uncertainty are declared. The central conclusion is therefore conditional but positive: a general scientific method for comparative interaction is justified. It is not a universal metric and does not imply that every pair of interactions is comparable. Its scientific strength lies in making equivalence, difference, trade-off, dominance, and incomparability explicit and reproducible. # 18. Reusable Artifact A - Comparison Contract ----------------------------------------------------------------------- **Field** **Required declaration** ----------------------------------- ----------------------------------- Identity Candidate interactions; versions; provenance; token or type comparison. Reference frame Target, task, users/agents, context, initial state, boundary, timescale, completion. Correspondence Entities, states, actions, events, outcomes, strategies, measures; ambiguous and unmapped items. Invariants Properties required to remain fixed by dimension. Transformations Renaming, reordering, abstraction, modality substitution, temporal rescaling, implementation substitution. Dimensions Selected comparison dimensions and reasons for inclusion or exclusion. Measures Measurands, instruments, scales, estimators, directionality, reliability, validity. Thresholds Equivalence bounds, minimum acceptable values, smallest effects of interest, vetoes. Uncertainty Record, mapping, sampling, model, instrument, and transport uncertainty. Evidence Formal proofs, records, experiments, qualitative evidence, standards conformance, expert review. Decision synthesis Optional weights, priorities, compensation, authority, sensitivity analysis. Scope Population, task, projection, context, time horizon, and invalidating conditions. ----------------------------------------------------------------------- # 19. Reusable Artifact B - Admissible Transformation Matrix --------------------------------------------------------------------------------- **Transformation** **Admissible?** **Conditions** **Affected dimensions** -------------------- ----------------- --------------------- -------------------- Renaming or Usually Preserve referents Semantic, structural identifier and operation substitution semantics. Visual restyling Sometimes No change to Semantic; possibly signaling, opportunity legibility, salience, or access. Modality No by default Requires Semantic may hold; substitution population-specific behavior/access may access and sequence differ evidence. Action reordering Sometimes Preserve causal Protocol, trace, dependencies and cost outcomes. Temporal rescaling Sometimes Preserve ordering and Structural but not relevant timing necessarily relations. performance Aggregation or Sometimes Declare omitted Type-level, not abstraction events and preserved token-level observables. Implementation Sometimes Preserve externally Semantic/formal; substitution relevant semantics, empirical latency, failure, revalidation needed authority, and state. Automation of user No by default Changes participant Interaction steps roles, coupling, structure and opportunity, and behavior strategy. Permission or policy No Changes admissible Opportunity and change action structure. semantics Training No for behavioral Changes agent state, Population/context intervention equivalence belief, strategy, and comparison required learning cost. --------------------------------------------------------------------------------- # 20. Reusable Artifact C - Minimal Reporting Template - Comparison claim: exact wording and typed relation. - Candidates and provenance. - Reference frame and validity domain. - Contracts used and gate results. - Correspondence mapping and unresolved items. - Invariants, transformations, tolerances, and vetoes. - Dimension-by-dimension measures, estimates, uncertainty, and evidence quality. - Subgroup and context variation. - Alternative explanations and falsifying evidence. - Optional decision rule, sensitivity analysis, and conditional recommendation. # 21. References Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking. MIT Press. Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Kluwer. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin. ISO 9241-11:2018. Ergonomics of human-system interaction - Part 11: Usability: Definitions and concepts. JCGM 100:2008. Evaluation of measurement data - Guide to the expression of uncertainty in measurement. Norman, D. A. (2013). The Design of Everyday Things, revised edition. Basic Books. Roy, B. (1991). The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31, 49-73. Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions. van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action. Springer. W3C. (2023). Web Content Accessibility Guidelines (WCAG) 2.2. Project paper. Representation, Invariance, and Projection: A Cross-Disciplinary Theory of What Representations Preserve, Transform, and Enable. Project paper. Ontology, Semantics, Representation, and Interpretation: Toward a Layered Theory of Computational Meaning. Project paper. Opportunity, Affordance, and Action Availability: Toward a Formal Account of What an Agent Can Perceive, Believe, and Do. Project paper. Interaction: Toward a General Theory of Interaction. Project paper. Behavior: Toward a Scientific Theory of Computational Behavior. Project paper. Measurement: Toward a Scientific Framework for Interaction Research. Project paper. Interaction Similarity: Toward a General Theory of Comparable Interactions. Project paper. Interaction Transfer: Toward a Theory of Experience and Adaptation. Project paper. Interaction Strategies: Toward a Theory of Behavioral Organization. Project paper. Formal Models of Computational Interaction: Toward a Mathematical Foundation. Project paper. Predicting Interaction: Toward a Predictive Theory of Computational Interaction. ======================================================================== ## FILE: docs/02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.md (934 lines, 43.6 KiB) ======================================================================== **Computational Interaction Science** *Foundations of a Scientific Theory of Computational Interaction* Final synthesis of the foundational research program **Final determination: Computational Interaction Science is best understood as an interdisciplinary synthesis.** # Abstract This paper integrates a sequence of foundational studies concerning scientific objects, representation, ontology, semantics, interpretation, opportunity, interaction, behavior, measurement, similarity, transfer, strategy, formal modeling, prediction, and comparative evaluation. Its purpose is to determine whether the accumulated evidence justifies Computational Interaction Science as an independent scientific discipline. The synthesis finds that computational interaction is a legitimate primary explanandum with a coherent ontology, explicit boundary conditions, formal representations, measurement contracts, falsifiable hypotheses, and a cumulative empirical program. The framework also contributes real explanatory organization by separating target from representation, semantic structure from interpretation, system-relative opportunity from agent-relative belief, interaction from behavior, records from evidence, and similarity from equivalence. However, the principal mechanisms remain substantially inherited from established disciplines: coupling and feedback from cybernetics and control; perception-action relations from ecological psychology; cognition and learning from cognitive science; formal transition and process semantics from computer science; authorization from security; measurement from psychometrics and metrology; and situated, distributed, and institutional organization from HCI, activity theory, and social science. The program has not yet demonstrated stable laws, unique mechanisms, autonomous methods, or predictive gains that cannot be obtained by disciplined integration of these fields. The evidence therefore supports Computational Interaction Science as an interdisciplinary scientific synthesis and research program, not yet as an independent discipline. # 1. Problem and Decision Rule The central question is not whether computational interaction is important, measurable, or theoretically rich. It is whether scientific understanding materially improves by recognizing a distinct discipline rather than treating the subject as an integrated research program within and across existing sciences. The decision must separate three claims that are often conflated: interaction can be a scientific object; a coherent theory of interaction can exist; and an autonomous discipline is necessary. The first two may be true while the third remains unsupported. The discipline claim is accepted only if the research program exhibits a sufficiently distinct explanatory object, ontology, mechanisms, formal and empirical methods, predictive or explanatory gains, cumulative problem structure, and boundaries that cannot be supplied adequately through integration of existing disciplines. Mere terminological unity, institutional convenience, or breadth of application is insufficient. # 2. Method of Synthesis The synthesis treats each preceding paper as a constrained contribution rather than as independent proof of the final conclusion. Definitions, formal contracts, and empirical claims were compared for consistency; duplicated constructs were normalized to established vocabulary; conflicts were retained where they mark genuine theoretical alternatives; and each proposed novelty was tested against reduction to adjacent theories. The final falsification test asks whether the complete framework can be reconstructed from existing disciplines without significant explanatory loss. If it can, a new discipline is not scientifically necessary. If integration fails because a distinctive object requires unique mechanisms, methods, or predictions, disciplinary independence becomes defensible. - Object test: Is computational interaction a stable and discriminating explanatory target? - Ontology test: Does the framework define a coherent set of entities and relations without unnecessary duplication? - Mechanism test: Are any generating mechanisms distinctive rather than borrowed or recombined? - Measurement test: Can constructs be operationalized with reproducible evidence and uncertainty? - Formal test: Can the theory be represented compositionally and analyzed? - Prediction test: Does it support scoped, testable forecasts and intervention claims? - Necessity test: Does the synthesis explain phenomena that strong integrated baselines cannot? # 3. Explanatory Object The primary explanatory object is not the interface, the user, the device, the software product, or isolated behavior. It is the computational interaction episode: a bounded interval in which distinguishable systems are coupled such that perturbations alter another system\'s possible or actual trajectory and the resulting configuration reciprocally or recurrently constrains a later trajectory within a declared boundary and timescale. This definition is strict enough to distinguish interaction from one-way causation, isolated action, passive observation, mere co-presence, and arbitrary input-output succession. Reciprocity may be asymmetric, delayed, probabilistic, environmentally mediated, or distributed over a sequence. Intentionality and communication are not necessary. Behavior is downstream but not synonymous: it is a bounded, temporally extended trajectory of observable or instrumentally recoverable changes, outputs, or regulated persistence attributed to a system under a declared observation model. A record is not behavior until detection, attribution, boundary selection, and interpretation have been made explicit. # 4. Complete Ontology ----------------------------------------------------------------------- **Concept** **Canonical role** ----------------------------------- ----------------------------------- **Domain** Declared entities, relations, constraints, processes, and possible states relevant to the study. **Participant** A distinguishable system assigned a role within an interaction boundary. **Environment** Relevant conditions and structures not assigned to a participant but participating in coupling. **State** A time-indexed assignment of relevant properties under a declared model. **Action** A bounded intervention or attributed act capable of affecting a trajectory. **Coupling** A dependency through which one system constrains another system\'s possible or actual trajectory. **Interaction episode** A bounded interval of reciprocal or recurrent constraint through coupling. **Semantic structure** Denotational, inferential, truth-conditional, or transition-relevant relations assigned to states or expressions. **Representation** A realized vehicle providing selective access to a target through mapping and interpretive practice. **Projection** An experimentally or analytically declared transformation from target structure to an observer-accessible form. **Observation** An instrument- and model-relative registration of selected aspects of an episode. **Interpretation** Contextual application or reconstruction of semantic relations by an agent or analytical process. **Opportunity profile** A coordinated typed description of possible, capable, permitted, enabled, reachable, exposed, signaled, believed, and recoverable action relations. **Behavioral trace** A temporally or causally ordered record of attributed events under a declared observation model. **Strategy** An inferred, temporally extended organization of conditional action selection, information use, resource allocation, and contingency response. **Experience state** Persistent changes in knowledge, skill, habit, calibration, artifact use, or coordination attributable to prior episodes. **Transfer** A source-dependent effect expressed in a distinct target context relative to a suitable counterfactual baseline. **Measurement** A rule-governed mapping from observations to values, estimates, or construct claims with declared uncertainty and admissible interpretation. **Similarity profile** A typed set of identity, equivalence, distance, or incomparability claims under declared observables and transformations. **Outcome** A state, criterion value, or consequence used to evaluate an episode or strategy. **Evidence** A traceable relation among records, observations, coding, estimates, assumptions, alternatives, and claims. ----------------------------------------------------------------------- # 5. Dependency Architecture The framework is relational rather than a one-way pipeline. Nevertheless, an analytical dependency order is required to prevent category errors: **Domain and ontology -\> semantic structure -\> representation and projection\ -\> observation and interpretation -\> opportunity profile -\> interaction episode\ -\> behavioral trace -\> strategy and adaptation -\> measurement, comparison, and prediction** Feedback operates in the reverse direction. Behavior changes state; outcomes change beliefs and strategies; repeated interaction changes experience; institutions alter permissions and representations; measurement choices alter what becomes visible as evidence. The arrows therefore mark analytical dependence, not deterministic causation. # 6. Foundational Assumptions 1. Targets and representations are distinguishable. A representation is never assumed identical to what it represents. 2. Equivalence is typed. Semantic, informational, structural, opportunity, behavioral, strategic, and measurement equivalence are distinct relations. 3. Interaction boundaries, participants, state variables, and timescales are analytical commitments and must be declared. 4. Representation does not determine behavior. Effects are mediated by interpretation, opportunity, goals, capabilities, history, and context. 5. System-relative availability and agent-relative belief are different. Feasibility, permission, exposure, signaling, belief, execution, and success must be separated. 6. Records are not self-interpreting. Observation, event detection, attribution, segmentation, and construct inference require explicit models. 7. Latent constructs are hypotheses supported by converging evidence, not properties read directly from traces. 8. Prediction is scoped and probabilistic. Predictability depends on target, horizon, information set, population, context, model class, and tolerated error. 9. Comparison requires a declared common frame. Incomparability is a valid result. 10. Existing terminology and mechanisms are preferred unless explanatory loss can be demonstrated. # 7. First Principles ----------------------------------------------------------------------- **Principle** **Statement** ----------------------------------- ----------------------------------- **Coupled constraint** Interaction exists when distinguishable systems reciprocally or recurrently constrain possible or actual trajectories through coupling within a declared episode. **Selective access** Every projection preserves, transforms, omits, emphasizes, or introduces access to target properties. **Typed opportunity** Action availability is not one set; it is a family of relations concerning feasibility, capability, authority, state, access, signal, belief, consequence, and recovery. **Situated interpretation** Meaningful uptake depends on context, prior experience, goals, conventions, and available evidence. **Trace discipline** Scientific claims must preserve the chain from records to observations, attributed events, measures, constructs, and explanations. **Compositionality with Episodes may compose sequentially, boundaries** concurrently, hierarchically, or through shared state only when boundary and interface conditions are explicit. **Typed comparison** Identity, equivalence, similarity, and ranking require declared observables, transformations, metrics, tolerances, and uncertainty. **Experience dependence** Prior episodes can change future beliefs, skills, habits, strategies, and coordination, but transfer must be established against a counterfactual baseline. **Bounded prediction** Near-term and tightly constrained phenomena are generally more predictable than latent, long-horizon, adaptive organization. **Comparative explanatory gain** The theory earns scientific necessity only if it outperforms strong integrated accounts in explanation, prediction, intervention, or unification. ----------------------------------------------------------------------- # 8. Generative and Explanatory Mechanisms The framework does not posit a single interaction mechanism. It organizes a family of established mechanisms operating at different levels. ----------------------------------------------------------------------- **Mechanism family** **Examples** ----------------------------------- ----------------------------------- **Dynamical** Coupling, feedback, control, synchronization, perturbation, stability, and recovery. **Computational** State transition, protocol execution, scheduling, concurrency, resource contention, and authorization. **Ecological** Perception of structured information, effectivities, affordances, and calibration. **Cognitive** Attention, memory, inference, learning, decision, planning, confidence, and strategy selection. **Representational** Encoding, abstraction, salience, externalization, transformation, and distributed computation. **Social and institutional** Norms, roles, authority, language, convention, division of labor, and organizational memory. **Developmental** Skill acquisition, habit formation, transfer, adaptation, and strategy evolution. **Measurement** Instrumentation, event detection, coding, estimation, aggregation, and uncertainty propagation. ----------------------------------------------------------------------- This breadth gives the synthesis coverage but weakens the case for disciplinary independence: the mechanisms are not uniquely interaction-scientific. The distinctive contribution is their disciplined coordination around a shared explanandum. # 9. Formal Architecture The recommended formal foundation is a layered observation-enriched probabilistic labeled transition system rather than a new calculus. **M = \** - N: participants and roles; S: factored system and environment states; A: typed actions and events; T: deterministic or probabilistic transition relation. - I and F: episode initiation and completion conditions; C: capability; P: permission; X: projection exposure; Sigma: signaling. - O: participant observation model; Y: instrument record model; B: belief state; G: goals or evaluation criteria; Mu: strategy or policy; R: recovery and reversibility relations. - Process-algebra operators supply composition, synchronization, hiding, and relabeling; event structures or Petri-net views preserve concurrency, conflict, and resource structure. - Equivalence and similarity remain typed: trace, simulation, bisimulation, testing, semantic, opportunity, behavioral, strategic, outcome, and measurement-relative relations are not interchangeable. The architecture is sufficient as a research representation because it separates system dynamics, projection, epistemic state, action selection, measurement, and recovery while permitting mappings to established formalisms. It is not evidence of a novel mathematical foundation. # 10. Evidence and Measurement Framework The empirical system of record is a three-contract chain: **Interaction Contract -\> Behavioral Evidence Contract -\> Measurement Contract** - The Interaction Contract declares participants, boundaries, states, coupling, preconditions, events, transitions, protocol, invariants, failure, recovery, completion, and uncertainty. - The Behavioral Evidence Contract declares records, detection rules, attribution, segmentation, trace ordering, alternative explanations, and inferential limits. - The Measurement Contract declares construct, measurand, unit, instrument, operationalization, transformation, scale, uncertainty, validity evidence, population, context, and prohibited interpretation. The canonical evidence ladder is: raw record; verified observation; coded observation; derived measure; model-based estimate; construct evidence; mechanism evidence; generalized claim. Every upward transition requires additional assumptions and possible falsifiers. # 11. Prediction Computational interaction supports predictive science only in a bounded sense. Low-level and well-specified phenomena such as motor time, choice under constrained alternatives, practiced task time, near-term transitions, and localized risks can support quantitative forecasts. Discovery, error, recovery, and abandonment are predictable probabilistically when state, task, projection, history, and population are adequately represented. Long-horizon adaptation, transfer, expertise, and strategy are weaker targets because latent state, nonstationarity, multiple viable policies, social context, and changing opportunity structures compound uncertainty. Predictive success does not establish mechanism, and intervention claims require causal assumptions beyond observational accuracy. A valid prediction must declare target, horizon, information set, population, context, model class, baseline, uncertainty, calibration, transport scope, and decision consequence. # 12. Methodological Framework 11. Declare the target phenomenon, episode boundary, participants, timescale, and explanatory question. 12. Specify ontology, semantic commitments, state variables, and admissible transitions. 13. Describe each representation or projection using a projection contract. 14. Construct typed opportunity profiles for relevant participants and states. 15. Collect records under an explicit observation and instrumentation model. 16. Detect and attribute behavioral events without importing latent explanations prematurely. 17. Operationalize constructs using measurement contracts and uncertainty budgets. 18. Compare interactions only after passing target, boundary, correspondence, measurement, and population comparability gates. 19. Fit explanatory and predictive models against strong domain-specific and integrated baselines. 20. Test transfer, strategy, and causal claims with appropriate counterfactual or intervention designs. 21. Report typed profiles, uncertainty, failures, and incomparability rather than forcing universal scores. 22. Update the shared ontology only when an irreducible explanatory gap has been demonstrated. # 13. Empirical Program ----------------------------------------------------------------------- **Program** **Core test** ----------------------------------- ----------------------------------- **Projection effects** Hold semantic target and feasible operations fixed; manipulate exposure or signaling; measure discovery, belief calibration, selection, error, and recovery. **Opportunity model gain** Compare models with and without typed opportunity variables on held-out behavior and recovery prediction. **Interaction boundary Test whether independent analysts reliability** identify comparable episode boundaries and coupling closure from the same records. **Trace attribution validity** Compare event and action coding across instruments, coders, and alternative observation models. **Similarity validity** Test whether typed similarity profiles predict transfer and performance better than implementation labels or aggregate distance. **Transfer mechanisms** Manipulate source-target structural relations; measure carrier persistence, accessibility, positive transfer, negative transfer, and far transfer. **Strategy inference** Validate inferred strategies against perturbations, counterfactual tasks, verbal evidence, and out-of-sample traces. **Formal-model adequacy** Evaluate whether the layered transition architecture represents observed concurrency, uncertainty, authorization, projection, and recovery without ad hoc exceptions. **Predictive boundaries** Map forecast accuracy and calibration across horizons, populations, novelty, and nonstationarity. **Comparative decision value** Test whether gate-and-profile evaluation produces more reliable design or policy decisions than aggregate usability scores. ----------------------------------------------------------------------- # 14. Relationship to Adjacent Sciences ----------------------------------------------------------------------- **Adjacent science** **Relationship** ----------------------------------- ----------------------------------- **Human-Computer Interaction** Primary institutional home; contributes interaction concepts, methods, usability, design, evaluation, and socio-technical analysis. The synthesis is narrower in explanatory ambition and broader in implementation independence. **Human Factors** Supplies performance, workload, error, safety, ergonomics, and systems evaluation. The synthesis adds explicit representation, opportunity, and interaction contracts. **Cognitive Science and Supply perception, memory, Psychology** reasoning, learning, decision, expertise, and skill mechanisms. The synthesis does not replace these mechanisms. **Ecological Psychology** Supplies agent-environment relations, affordances, and ecological information. It does not by itself encode authorization, projection, formal state, or measurement layers. **Cybernetics and Control** Supply coupling, feedback, regulation, stability, and controllability. They remain foundational for dynamical explanation. **Computer Science and Formal Supply computation, transition Methods** systems, process semantics, protocols, verification, concurrency, and access control. They provide the formal backbone. **Information Science and Supply representation, information Visualization** organization, retrieval, external cognition, and access. The synthesis adds typed behavioral and opportunity consequences. **Learning Sciences and Expertise Supply transfer, adaptation, skill, Research** practice, and distributed learning mechanisms. **Activity Theory and Distributed Supply mediated, historical, Cognition** organizational, and socially distributed units of analysis. **Economics and Decision Theory** Supply choice sets, preferences, utility, risk, games, and policy analysis, but generally abstract from projection and interpretation unless extended. ----------------------------------------------------------------------- # 15. Explanatory Gain The synthesis provides genuine explanatory gain in four forms. - Disambiguation: it prevents ontology, semantics, representation, interpretation, opportunity, behavior, and evidence from being collapsed. - Cross-level linkage: it connects formal system properties with projection, observer access, belief, action, trace, learning, and institutional constraint. - Comparability: it supplies contracts and typed profiles for comparing implementations without assuming informational or semantic equivalence entails behavioral equivalence. - Research coordination: it converts scattered constructs into cumulative artifacts that can be tested, reused, and revised. These are substantive contributions. They justify a named framework and research program. They do not yet prove theoretical autonomy because the gains arise mainly from disciplined integration and boundary management rather than from a uniquely interaction-specific mechanism. # 16. Final Falsification of Disciplinary Necessity ----------------------------------------------------------------------- **Criterion** **Assessment** ----------------------------------- ----------------------------------- **Distinct object** Pass. Computational interaction is a coherent primary explanandum with identifiable episodes, boundaries, and evidence. **Coherent ontology** Pass provisionally. The ontology is internally consistent and cumulative, though many entities are inherited. **Unique mechanisms** Fail. No mechanism has been shown to belong uniquely to computational interaction or to resist explanation by integrated adjacent sciences. **Autonomous methods** Fail. Experimental, observational, formal, psychometric, causal, and predictive methods are inherited and adapted. **Formal independence** Fail. The recommended foundation is explicitly a layered composition of established formalisms rather than a new calculus. **Predictive superiority** Not established. Scoped prediction is possible, but incremental gain over strong integrated baselines remains an empirical hypothesis. **Explanatory necessity** Not established. The synthesis improves coordination and comparison, but current evidence does not show that existing disciplines cannot jointly explain the phenomena. **Cumulative empirical community** Emergent rather than demonstrated. The framework defines a program, but replication, benchmark tasks, shared datasets, and sustained institutional practice remain future work. ----------------------------------------------------------------------- # 17. Research Agenda 23. Publish stable machine-readable schemas for the Interaction, Opportunity, Behavioral Evidence, Measurement, Similarity, Transfer, Strategy, Prediction, and Comparison contracts. 24. Create benchmark interaction episodes spanning GUI, command, API, conversational, multimodal, accessible, collaborative, and safety-critical systems. 25. Develop shared annotation datasets preserving raw records, observation models, attributed events, uncertainty, and rival interpretations. 26. Test reliability of episode boundaries, opportunity coding, event attribution, and strategy inference across laboratories. 27. Evaluate whether typed opportunity and projection variables improve explanation and prediction beyond established HCI, cognitive, control, and process models. 28. Develop causal experiments separating semantic preservation, projection, signaling, capability, permission, and belief. 29. Test transfer and adaptation across representation, modality, device, task, and institutional context using source-target similarity contracts. 30. Formalize compositional mappings among transition systems, event structures, process algebra, probabilistic models, and measurement traces. 31. Establish non-compensatory criteria for accessibility, safety, authorization, and irreversible harm in comparative evaluation. 32. Conduct preregistered multi-site replications before making discipline-level claims. # 18. Open Problems - Boundary ontology: when do analyst-chosen episode boundaries correspond to stable causal or functional organization? - Reciprocity threshold: what minimum recurrent closure distinguishes interaction from extended one-way causation? - Emergent action vocabularies: how should open-ended interaction be modeled when available actions are constructed during activity? - Collective agency: how should participant identity and strategy be represented in distributed human-machine organizations? - Semantic grounding: under what conditions can semantic state be specified independently of interpretive practice? - Opportunity measurement: can believed, signaled, and recoverable action relations be estimated reliably across populations and modalities? - Mechanism identification: can traces distinguish competing cognitive, ecological, institutional, and computational mechanisms? - Nonstationarity: how should models remain valid when participants, systems, policies, and conventions co-adapt? - Ethics and power: how should coercion, manipulation, exclusion, and institutional authority enter the ontology without being reduced to preference or performance? - Disciplinary threshold: what empirical achievements would convert an interdisciplinary synthesis into a scientifically autonomous field? # 19. Canonical Vocabulary ----------------------------------------------------------------------- **Term** **Definition** ----------------------------------- ----------------------------------- **Computational interaction** Interaction in which at least one participant, coupling mechanism, state transformation, or mediating environment is computationally realized. **Computational Interaction The interdisciplinary scientific Science** program that explains computational interaction episodes, their representations, opportunity structures, behaviors, adaptations, measurements, comparisons, and predictions. **Projection** A declared mapping from target structure to an observer-accessible representation, including preserved, transformed, omitted, and introduced properties. **Opportunity** An umbrella analytical profile coordinating typed action-availability relations; not a primitive or synonym for affordance. **Interaction preservation** Preservation of declared coupling, protocol, boundaries, and reciprocal constraint relations under transformation. **Behavioral preservation** Preservation of a declared behavioral relation or distribution under a specified observation model and tolerance. **Measurement equivalence** Evidence that an operationalization has sufficiently invariant meaning and error properties across compared contexts. **Comparability** Satisfaction of the target, boundary, correspondence, observation, measurement, population, and uncertainty conditions required for a defensible comparison. **Explanatory gain** Improvement in mechanism discrimination, unification, intervention, or anomaly resolution relative to a strong baseline. **Predictive gain** Out-of-sample improvement in accuracy, calibration, transport, or decision utility relative to a declared baseline. ----------------------------------------------------------------------- # 20. Conclusion The research program has crossed the threshold from a collection of intuitions to a coherent scientific framework. It possesses a legitimate explanatory object, cumulative ontology, first principles, formal representation, measurement architecture, falsifiable claims, comparative method, and empirical agenda. It can support rigorous science. The evidence does not, however, establish the necessity of an independent discipline. The framework\'s strongest achievements are synthesis, disambiguation, cross-level linkage, and methodological coordination. Its mechanisms, mathematical tools, measurement theories, and empirical methods remain substantially inherited from HCI, cognitive science, psychology, ecological psychology, cybernetics, control, computer science, information science, learning science, and social theory. Predictive and explanatory gains over strong integrated baselines have been proposed but not yet demonstrated through a cumulative empirical record. **Final determination 2: Computational Interaction Science is best understood as an interdisciplinary synthesis.** This conclusion is not a rejection of the framework. It identifies its scientifically defensible status. The appropriate next step is not disciplinary declaration but empirical competition: the synthesis should be tested against the best combined explanations available from adjacent sciences. Independent disciplinary recognition would become justified only if that program demonstrates durable mechanisms, methods, predictions, or explanatory successes that integration alone cannot supply. # References Ashby, W. R. (1956). An Introduction to Cybernetics. Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking. Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7-19. Cousot, P., & Cousot, R. (1977). Abstract interpretation: A unified lattice model for static analysis. Engestrom, Y. (1987). Learning by Expanding. Gaver, W. W. (1991). Technology affordances. CHI \'91. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Harel, D. (1987). Statecharts: A visual formalism for complex systems. Hutchins, E. (1995). Cognition in the Wild. ISO 9241-11:2018. Ergonomics of human-system interaction - Usability: Definitions and concepts. Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Norman, D. A. (2013). The Design of Everyday Things, revised edition. Pearl, J. (2009). Causality, 2nd ed. Shannon, C. E. (1948). A mathematical theory of communication. Suchman, L. A. (1987). Plans and Situated Actions. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction, 2nd ed. Tinbergen, N. (1963). On aims and methods of ethology. Winskel, G. (1987). Event structures. Foundational program papers: How Sciences Define Their Objects; Can Interaction Become a Primary Scientific Object; Representation, Invariance, and Projection; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability; Interaction; Behavior; Measurement; Interaction Similarity; Interaction Transfer; Interaction Strategies; Formal Models of Computational Interaction; Predicting Interaction; Comparative Interaction. ======================================================================== ## FILE: docs/05_Publication/Bibliography_Audits/README.md (8 lines, 0.6 KiB) ======================================================================== # Bibliography Audits and Reports Index **Status:** Supporting reference indexes (views only) The canonical audit and report output files are maintained under the normalized bibliography package directory to avoid duplication and drift. Please refer to their authoritative locations: - **Audit Datasets:** [docs/04_Reference/Bibliography/Verified_v1.1.2/02_Audits/](../../04_Reference/Bibliography/Verified_v1.1.2/02_Audits/) - **Reports and Manuals:** [docs/04_Reference/Bibliography/Verified_v1.1.2/03_Reports/](../../04_Reference/Bibliography/Verified_v1.1.2/03_Reports/) ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Appendix_A_Candidate_Version_2.0_Changes.md (12 lines, 0.3 KiB) ======================================================================== # Appendix A - Candidate Version 2.0 Changes ## Status No candidate theoretical improvements were incorporated or proposed during this editorial normalization pass. ## Rule Future theory changes must be recorded here with rationale, evidence, affected concepts, migration impact, and corpus-wide dependencies before Version 2.0 consideration. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Consistency_Report.md (19 lines, 0.5 KiB) ======================================================================== # Consistency Report ## Checks performed Markdown heading hierarchy; canonical contract capitalization; trailing whitespace; blank-line structure; release labeling; figure-catalog identifier format; presence of requested source and derivative artifacts. ## Results No unresolved heading-hierarchy or canonical contract-capitalization defects were detected in authored Markdown files. ## Boundary This pass verifies presentation-level consistency. It does not reinterpret or validate theory, bibliography authority, or empirical claims. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Cross_Reference_Report.md (20 lines, 0.6 KiB) ======================================================================== # Cross-Reference Report ## Scope Reviewed internal references expressed as file paths, canonical artifact names, figure identifiers, bibliography-system references, and contract names. ## Result No cross-reference target was intentionally renamed. Existing literal paths, citation keys, schema fields, and identifiers were preserved. Named contract references were normalized without changing targets. ## Outstanding work Word field-based cross-references and equation numbering remain dependent on the later publication-copyedit pass because the attached repository contains infrastructure documents rather than the complete paper corpus. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Editorial_Change_Report.md (72 lines, 2.4 KiB) ======================================================================== # Editorial Change Report ## Scope This report records changes made to the attached publication-infrastructure repository. No ontology, first principle, contract semantics, or formal semantics were modified. ## Changes - **Editorial** - 02_Citation_Evidence/Citation_Map.md: Canonical artifact capitalization (1 occurrence(s)) - **Editorial** - 02_Citation_Evidence/Citation_Map.md: Canonical artifact capitalization (1 occurrence(s)) - **Editorial** - 02_Citation_Evidence/Citation_Map.md: Improved citation-map record separation (Inserted spacing between definition, origin, and candidate sources) - **Editorial** - 02_Citation_Evidence/Citation_Map.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 02_Citation_Evidence/Reading_Guide.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 03_Handbooks/Experimental_Handbook.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 03_Handbooks/Measurement_Handbook.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 03_Handbooks/Replication_Handbook.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 04_Templates/Preregistration_Template.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 04_Templates/Study_Reporting_Template.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 07_Guides/Author_Guide.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 07_Guides/Publication_Template.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 08_Reports/Completeness_Report.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 08_Reports/Maintenance_Report.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 08_Reports/Publication_Readiness_Assessment.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - 08_Reports/Quality_Report.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - README.md: Whitespace and Markdown structure normalization (Applied) - **Editorial** - README.md: Release label and editorial status notice (v1.0.0 -\> v1.1.1; theory remains Version 1.0) ## Classification summary Editorial changes: 18 Structural changes: 0 Normative changes: 0 ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Outstanding_Editorial_Issues.md (25 lines, 0.8 KiB) ======================================================================== # Outstanding Editorial Issues ## Repository boundary The attached archive contains the publication-infrastructure repository, not the complete Knowledge System of Record and research-paper corpus. Corpus-wide definition and paper-heading verification therefore cannot be completed from this archive alone. ## Bibliography Authority validation, duplicate resolution, and missing metadata remain separate bibliographic-verification work. ## Figures Only one reusable canonical figure is present. Source figures, editable originals, captions, accessibility text, and rights status remain incomplete. ## DOCX fields Generated DOCX files use static headings and text. Dynamic Word cross-reference fields, equation sequences, and indexes require the final publication assembly. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Publication_Readiness_Assessment.md (24 lines, 0.7 KiB) ======================================================================== # Publication Readiness Assessment ## Determination **Publication infrastructure is editorially normalized for controlled Version 1.0 use, subject to bibliographic authority validation, figure completion, and final publication assembly.** ## Passed Terminology presentation, canonical contract capitalization, Markdown structure, heading syntax, style policy, release labeling, and derivative-document styling. ## Not evaluated Normative theory, full Knowledge System of Record consistency, complete research-paper hierarchy, bibliographic authority, and empirical validity. ## Next gate Run bibliographic verification, then perform the final publication copyedit on the complete assembled corpus. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Style_Guide.md (101 lines, 2.7 KiB) ======================================================================== # Computational Interaction Science Editorial Style Guide ## Authority and scope The Knowledge System of Record governs terminology and definitions. Research papers and infrastructure artifacts provide provenance, evidence, and implementation guidance. Editorial changes may improve presentation but may not alter ontology, first principles, contracts, or formal semantics. ## Language - Use American English. - Use the Oxford comma. - Prefer direct, declarative sentences. - Use ASCII hyphens and dashes in machine-readable and cross-platform artifacts. - Avoid contractions in normative and technical prose. ## Canonical terms - Preserve the exact spelling of canonical concepts. - Capitalize named artifacts: Projection Contract, Opportunity Contract, Interaction Contract, Behavioral Evidence Contract, Measurement Contract, Similarity Contract, Transfer Contract, Strategy Contract, Prediction Contract, and Comparison Contract. - Use lower case for generic mentions of concepts unless beginning a sentence or naming an artifact. - Do not create local synonyms or redefine canonical concepts. ## Headings - Use one level-1 heading per standalone document. - Use sentence case for section headings. - Do not skip heading levels. - Separate headings from body text with one blank line. ## Lists and tables - Use bullets for parallel items and numbered lists for procedures or ranked sequences. - Keep list items grammatically parallel. - Use sentence punctuation for complete sentences; omit terminal punctuation for short fragments. - Give every table a descriptive title when presented in publication form. ## Figures - Assign stable identifiers in the form FIG-NNN. - Use captions in the form Figure N. Descriptive sentence. - Record source artifact, editable source, export formats, version, concept links, rights status, and accessibility text. - Refer to figures by number, not by position. ## Equations, notation, and code - Define every symbol at first use and preserve the canonical Symbol Table. - Number equations only when referenced later. - Use fenced code blocks with a language identifier where applicable. - Preserve literal identifiers, file paths, citation keys, and schema fields exactly. ## Citations and references - Use the Master Bibliography as the system of record. - Use one canonical citation key per work. - Do not infer missing bibliographic metadata. - Prefer primary and authoritative sources. ## Change control - Classify changes as Editorial, Structural, or Normative. - Normative changes are prohibited in Version 1.1.1. - Record theoretical improvements only in Appendix A - Candidate Version 2.0 Changes. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/Terminology_Normalization_Report.md (19 lines, 0.6 KiB) ======================================================================== # Terminology Normalization Report ## Canonical policy Named contracts are capitalized as canonical artifacts. Canonical concepts retain their established spelling. Generic concepts remain lower case in ordinary prose. ## Applied normalizations Projection Contract, Interaction Contract, Measurement Contract, Behavioral Evidence Contract, Similarity Contract, Transfer Contract, Strategy Contract, Prediction Contract, and Comparison Contract were normalized where present. ## Prohibited changes No canonical definition, concept identifier, ontology relation, or formal symbol was changed. ======================================================================== ## FILE: docs/05_Publication/Editorial_Reports/build_summary.json (11 lines, 0.2 KiB) ======================================================================== { "release": "1.1.1", "theory_version": "1.0", "files": 93, "markdown_normalized": 25, "structural_changes": 0, "normative_changes": 0, "docx_rendered_and_reviewed": 25, "rendered_pages_reviewed": 56, "zero_byte_files": 0 } ======================================================================== ## FILE: docs/05_Publication/Publication_Reports/Completeness_Report.md (29 lines, 0.6 KiB) ======================================================================== # Completeness Report - Bibliography entries: 312 - Core author/title/year complete: 312 - DOI present and syntactically valid: 15 - Valid ISBN checksum: 3 - Volume present: 53 - Issue present: 53 - Page range present: 112 - Duplicate-title groups requiring review: 35 - Canonical concepts mapped: 54 - Evidence-register claims: 54 - Indexed figures: 16 ## Limitation Syntactic validation is not publisher-record validation. The package does not claim that every missing DOI or ISBN was recoverable. Unverified fields remain blank. ======================================================================== ## FILE: docs/05_Publication/Publication_Reports/Maintenance_Report.md (21 lines, 0.6 KiB) ======================================================================== # Maintenance Report ## Systems of record - Master bibliography: 01_Bibliography/Master_Bibliography.bib - Concept-source mapping: 02_Citation_Evidence/Concept_Source_Matrix.csv - Evidence register: 02_Citation_Evidence/Evidence_Register.csv - Dataset schema: 05_Dataset_Schema/interaction_study.schema.json - Figure catalog: 06_Figures/Figure_Catalog.csv ## Release workflow Propose -\> classify editorial/structural/normative -\> verify dependencies -\> update source of record -\> regenerate derivatives -\> run audits -\> review -\> checksum -\> release. Normative theory changes are not integrated into Version 1.0. ======================================================================== ## FILE: docs/05_Publication/Publication_Reports/Publication_Readiness_Assessment.md (25 lines, 0.9 KiB) ======================================================================== # Publication Readiness Assessment **Determination: publication infrastructure is suitable for internal Version 1.0 use, subject to bibliographic and evidential verification before external scholarly publication.** The package provides the requested infrastructure without modifying theory. It is sufficient for controlled authoring, study design, replication planning, data structuring, and reference maintenance. It is not a claim that all 600 bibliographic records have been authority-validated or that all canonical constructs have empirical validation. ## Blocking items for external release 1. Authority validation of references most central to canonical claims. 2. Human review of duplicate groups and candidate DOI/ISBN metadata. 3. Ratification of concept-source mappings and evidence confidence. 4. Figure licensing, captions, editable sources, and accessibility text. 5. Pilot validation of schemas and templates. ======================================================================== ## FILE: docs/05_Publication/Publication_Reports/Quality_Report.md (24 lines, 0.9 KiB) ======================================================================== # Quality Report ## Strengths The corpus has stable canonical concept identifiers, a master bibliography, machine-readable citation and evidence tables, explicit measurement and replication guidance, and reusable reporting and dataset schemas. ## Risks The original bibliography contains many reference-string-derived records with sparse structured metadata. Concept-to-source links are heuristic until manually ratified. Figure extraction is incomplete because captions, licenses, and editable sources are not uniformly available. The experimental handbooks operationalize existing contracts but do not validate constructs empirically. ## Quality gates Before external publication: verify high-priority references against authoritative records; ratify the evidence register; assign figure rights/status; pilot the dataset schema; and test reporting templates in at least one study. ======================================================================== ## FILE: docs/05_Publication/Style_and_Authoring/Author_Guide.md (20 lines, 0.8 KiB) ======================================================================== # Author Guide Use canonical terms and identifiers from the glossary and ontology. Import definitions by reference; do not redefine them. Separate observations, measurements, inferences, and conclusions. Identify every contract used. State boundaries, timescale, population, task, projection, context, uncertainty, and falsification conditions. Cite primary sources where possible and cite the canonical corpus for project-specific synthesis. Record proposed theoretical changes only as Version 2.0 candidates. ## Citation style Use one citation key per work from the master bibliography. Do not create local variants. Verify identifiers before publication. ## Figures and tables Assign stable IDs, captions, source, version, and concept links. Provide editable source plus PDF/PNG exports. ======================================================================== ## FILE: docs/05_Publication/Style_and_Authoring/Publication_Template.md (27 lines, 0.3 KiB) ======================================================================== # Title ## Subtitle Version: Status: Draft \| Candidate \| Canonical Canonical dependencies: ## Abstract ## Scope ## Definitions ## Assumptions ## Claims ## Formalization ## Evidence ## Evaluation and falsification ## Limitations ## Version 2.0 candidates (informative only) ## References ======================================================================== ## FILE: docs/05_Publication/Style_and_Authoring/Reference_Maintenance_Guide.md (26 lines, 0.8 KiB) ======================================================================== # Reference Maintenance Guide 1. The master BibTeX file is the system of record. 2. Add a reference only after title, creator, year, and work type are verified. 3. Prefer publisher pages, Crossref, DataCite, library catalogs, standards bodies, and the work itself. 4. Normalize DOI as the bare identifier; store resolvable URL separately if needed. 5. Validate ISBN checksums and edition specificity. 6. Never infer issue or page ranges from neighboring records. 7. Merge duplicates only after work identity is confirmed. 8. Preserve aliases and retired citation keys in a migration table. 9. Regenerate CSL JSON and formatted references after each approved change. 10. Run completeness, duplicate, identifier-format, and link checks before release. ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Appendices/Appendix_A_Candidate_Version_2.0_Changes.md (9 lines, 0.8 KiB) ======================================================================== # Appendix A - Candidate Version 2.0 Changes The following items were discovered during integration and were not incorporated into Version 1.0: 1. Evaluate whether "Foundations of Computational Interaction" remains the preferred program name after empirical validation; the current synthesis supports an interdisciplinary research program rather than disciplinary autonomy. 2. Consider formally ratifying the distinction between broad ordinary-language interaction and the strict interaction-episode research definition. 3. Evaluate whether transfer should become a first-class ontology node in a future normative revision. It is currently represented primarily through contracts and research papers. These are proposals for later review, not changes to the Version 1.0 theory. ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Change_Report.md (68 lines, 3.4 KiB) ======================================================================== **Change Report** Version 1.0.0-integration.1 Version: 1.0.0-integration.1 # Changes # Appendix A - Candidate Version 2.0 Changes - Consider whether "Computational Interaction Science" remains the preferred program name after empirical validation; current evidence supports interdisciplinary synthesis rather than disciplinary autonomy. - Consider a formally ratified distinction between broad ordinary-language interaction and the strict interaction-episode research definition. - Evaluate whether transfer should become a first-class ontology node in a future normative revision; it is presently represented primarily through contracts and papers. # Change register ------------------------------------------------------------------------------- Artifact Class Change Drift control -------------------- ---------------------- ----------------- ----------------- Canonical glossary Structural Consolidated 49 No canonical glossary concepts definition was into one enriched replaced by new record with IDs, theory. provenance, status, measurement and graph fields. Canonical ontology Structural Merged relational Relations limited ontology, to those already glossary expressed in the dependencies, and corpus. contracts stack. Vocabulary/indexes Editorial/Structural Normalized Deprecated terms identifiers, are warnings, not aliases, and redefinitions. source paths. Knowledge graph Structural Materialized No new canonical ontological concepts and category declared introduced. relations in CSV, GraphML, JSON-LD, Mermaid, and PDF. Cross-reference Structural Mapped concept Occurrence counts matrix mentions to all are provenance 16 research aids, not papers. evidential strength scores. Figure/artifact Editorial Inventoried No source indexes figures, tables, artifact media, paths, modified. hashes, and authority roles. ------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Consistency_Report.md (80 lines, 4.6 KiB) ======================================================================== **Consistency Report** Version 1.0.0-integration.1 Version: 1.0.0-integration.1 # Findings # No-change confirmations No canonical definitions were replaced with newly invented theory. No research paper or source artifact was modified. # Issue register --------------------------------------------------------------------------------- Issue Finding Classification Required disposition -------------------- ------------------- -------------------- ------------------- Authority status Current ontology Structural Ratify or and glossary are governance explicitly label marked provisional inconsistency the integrated drafts, while the outputs as release archive is labeled candidates. Version 1.0.0. Contract naming The Opportunity Terminology Correct as an Contract section inconsistency editorial label begins with the change in the words "Projection contracts source contract." during specification work. Contract coverage The consolidated Incomplete Extract and contracts file consolidation normalize the includes Projection Comparison Contract through Prediction in the formal but does not yet specification contain a fully phase. normalized Comparison Contract. Concept provenance Some glossary terms Provenance Manually ratify occur broadly limitation originating-paper across papers, ownership during making automated publication audit. originating-paper attribution approximate. Supporting Concept-source Reference Complete metadata literature matrix coverage is incompleteness and concept-source uneven and some validation in the entries are research represented mainly infrastructure through document phase. tables. Operationalization Several constructs Incomplete Address in the are operationalization experimental operationalizable handbook; do not in principle but change definitions. lack one ratified measurement protocol. Figure captions Many DOCX files Figure governance Assign canonical contain embedded gap figure IDs and media without captions in the explicit Word figure-library caption paragraphs. phase. Theory maturity No concept is Publication Retain Proposed marked Validated or readiness limitation status until Canonical in the empirical source glossary. validation or formal ratification. --------------------------------------------------------------------------------- ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Impact_Analysis.md (19 lines, 0.6 KiB) ======================================================================== **Impact Analysis** Version 1.0.0-integration.1 Version: 1.0.0-integration.1 # Impact No source document was overwritten. The integrated outputs create a candidate authority layer for review. Direct dependents are the formal specification, research infrastructure, experimental handbook, encyclopedia, and final publication audit. Backward compatibility is preserved because source wording remains available and canonical IDs are additive. # Affected artifacts Canonical ontology, glossary, vocabulary, definition index, graphs, matrices, indexes, and downstream specification work. ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Publication_Readiness_Assessment.md (27 lines, 0.9 KiB) ======================================================================== **Publication Readiness Assessment** Version 1.0.0-integration.1 Version: 1.0.0-integration.1 # Assessment Assessment: Publication ready only as a reconciled release candidate, not yet as a ratified normative standard. Strengths: coherent authority structure; 54 normalized concepts; 42 declared relations; 16 research papers indexed; complete artifact hashing and provenance paths. Blocking items: provisional status of ontology/glossary; incomplete normalized Comparison Contract; uneven reference metadata; absence of ratified empirical validation for Proposed constructs; figure governance gaps. Readiness estimate: 78/100. This score reflects corpus completeness and internal coherence, not empirical validation of the theory. # Required next gate Complete and ratify the formal specification, bibliography metadata audit, experimental handbook, and final consistency audit. ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Source_Data/concepts.json (3588 lines, 94.0 KiB) ======================================================================== [ { "id": "domain-commitments", "term": "Domain commitments", "status": "Proposed", "definition": "A set of commitments about admissible entities, categories, relations, identity conditions, modalities, and constraints in a domain. In computational work, these commitments may be approximated through ontologies, schemas, contracts, types, or model definitions, but none of those artifacts is automatically a philosophical ontology.", "boundary": "Domain commitments specify what the model admits. They do not by themselves assign meaning, produce a representation, or determine interpretation.", "paper_hits": [ [ "05", "Ontology, Semantics, Representation, and Interpretation", 3 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 1 ] ], "originating_paper": "Ontology, Semantics, Representation, and Interpretation", "supporting_papers": [ "Ontology, Semantics, Representation, and Interpretation", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?" ], "aliases": [ "ontology commitments" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [], "dependents": [ "System state", "Semantic assignment" ], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "system-state", "term": "System state", "status": "Proposed", "definition": "The physical, computational, social, or modeled condition of a declared system at a particular time.", "boundary": "State is not synonymous with data, meaning, representation, or observation. A state becomes content-bearing only under a specified semantics.", "paper_hits": [ [ "06", "Opportunity, Affordance, and Action Availability", 3 ], [ "05", "Ontology, Semantics, Representation, and Interpretation", 2 ], [ "07", "Interaction", 1 ], [ "12", "Interaction Strategies", 1 ], [ "14", "Predicting Interaction", 1 ] ], "originating_paper": "Opportunity, Affordance, and Action Availability", "supporting_papers": [ "Opportunity, Affordance, and Action Availability", "Ontology, Semantics, Representation, and Interpretation", "Interaction", "Interaction Strategies", "Predicting Interaction" ], "aliases": [ "state" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "Domain commitments", "State transition" ], "dependents": [ "Projection", "Opportunity profile" ], "contracts": [ "Projection Contract", "Opportunity Contract", "Interaction Contract", "Behavioral Evidence Contract", "Measurement Contract", "Similarity Contract", "Transfer Contract", "Strategy Contract", "Prediction Contract" ], "formal_mappings": [ "Layered observation-enriched probabilistic labeled transition system" ], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "semantic-assignment", "term": "Semantic assignment", "status": "Proposed", "definition": "A rule-governed assignment of content, denotation, truth conditions, inferential consequences, or transition behavior to expressions, states, signs, or operations within a specified system and domain.", "boundary": "Formal semantic assignment is distinct from a person’s interpretation or understanding.", "paper_hits": [ [ "05", "Ontology, Semantics, Representation, and Interpretation", 2 ] ], "originating_paper": "Ontology, Semantics, Representation, and Interpretation", "supporting_papers": [ "Ontology, Semantics, Representation, and Interpretation" ], "aliases": [ "formal semantics" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "Domain commitments" ], "dependents": [ "Semantic state", "Projection" ], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "semantic-state", "term": "Semantic state", "status": "Proposed", "definition": "The content-bearing assignments and relations currently licensed by a specified semantics for a system or discourse state.", "boundary": "No observer-independent semantic state is assumed without an explicit theory and scope.", "paper_hits": [ [ "05", "Ontology, Semantics, Representation, and Interpretation", 7 ], [ "04", "Representation, Invariance, and Projection", 1 ], [ "16", "Foundations of Computational Interaction", 1 ] ], "originating_paper": "Ontology, Semantics, Representation, and Interpretation", "supporting_papers": [ "Ontology, Semantics, Representation, and Interpretation", "Representation, Invariance, and Projection", "Foundations of Computational Interaction" ], "aliases": [], "deprecated": [], "observable": "No - latent/inferred", "latent": "Yes", "measurement": "Requires latent-variable model", "dependencies": [ "Semantic assignment" ], "dependents": [], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "information", "term": "Information", "status": "Proposed", "definition": "A typed measure or characterization of distinctions, correlations, descriptions, or content relative to a specified source, code, semantic relation, probability model, or use.", "boundary": "Information is not a synonym for stored variables, data, meaning, semantic state, or interpretation. Every claim that information is preserved must name the information theory, source, code, task, or relevance criterion.", "paper_hits": [ [ "05", "Ontology, Semantics, Representation, and Interpretation", 29 ], [ "04", "Representation, Invariance, and Projection", 24 ], [ "12", "Interaction Strategies", 21 ], [ "14", "Predicting Interaction", 13 ], [ "01", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", 10 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 10 ], [ "06", "Opportunity, Affordance, and Action Availability", 6 ], [ "09", "Measurement", 4 ], [ "07", "Interaction", 3 ], [ "16", "Foundations of Computational Interaction", 3 ], [ "03", "How Sciences Define Their Objects", 2 ], [ "13", "Formal Models of Computational Interaction", 1 ] ], "originating_paper": "Ontology, Semantics, Representation, and Interpretation", "supporting_papers": [ "Ontology, Semantics, Representation, and Interpretation", "Representation, Invariance, and Projection", "Interaction Strategies", "Predicting Interaction", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM" ], "aliases": [], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [], "dependents": [], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "representation", "term": "Representation", "status": "Proposed", "definition": "A materially or formally realized vehicle that provides selective access to a declared target through a mapping or correspondence and an interpretive practice.\n\nA representation may preserve, transform, omit, or introduce structure.", "boundary": "A representation is not identical with its target. Equal reference does not imply semantic, inferential, behavioral, or interactional equivalence.", "paper_hits": [ [ "04", "Representation, Invariance, and Projection", 60 ], [ "01", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", 30 ], [ "05", "Ontology, Semantics, Representation, and Interpretation", 25 ], [ "11", "Interaction Transfer", 15 ], [ "16", "Foundations of Computational Interaction", 12 ], [ "12", "Interaction Strategies", 10 ], [ "09", "Measurement", 8 ], [ "03", "How Sciences Define Their Objects", 6 ], [ "08", "Behavior", 6 ], [ "10", "Interaction Similarity", 6 ], [ "13", "Formal Models of Computational Interaction", 5 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 4 ], [ "06", "Opportunity, Affordance, and Action Availability", 4 ], [ "14", "Predicting Interaction", 3 ], [ "15", "Comparative Interaction", 3 ], [ "07", "Interaction", 2 ] ], "originating_paper": "Representation, Invariance, and Projection", "supporting_papers": [ "Representation, Invariance, and Projection", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", "Ontology, Semantics, Representation, and Interpretation", "Interaction Transfer", "Foundations of Computational Interaction" ], "aliases": [ "representational vehicle" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "Projection" ], "dependents": [ "Interpretation" ], "contracts": [], "formal_mappings": [], "examples": [ "A table and graph that selectively expose the same declared target." ], "counterexamples": [ "The target itself, treated as identical with its representation." ], "supporting_literature": [] }, { "id": "projection", "term": "Projection", "status": "Proposed analytical role", "definition": "A declared transformation from a target description, system state, or semantic assignment into an accessible representational form.\n\nA projection contract specifies:\n\n- target and authority;\n- mapping or construction rule;\n- interpretation assumptions;\n- preserved properties;\n- transformed properties;\n- omitted properties;\n- introduced properties;\n- available operations;\n- observer assumptions;\n- intended use;\n- context and scope;\n- uncertainty, tolerance, and failure conditions.", "boundary": "Projection coordinates established concepts such as views, abstractions, encodings, lenses, simulations, model morphisms, and renderings. It is not a new metaphysical substance.", "paper_hits": [ [ "06", "Opportunity, Affordance, and Action Availability", 32 ], [ "04", "Representation, Invariance, and Projection", 24 ], [ "13", "Formal Models of Computational Interaction", 14 ], [ "16", "Foundations of Computational Interaction", 10 ], [ "14", "Predicting Interaction", 7 ], [ "09", "Measurement", 6 ], [ "05", "Ontology, Semantics, Representation, and Interpretation", 5 ], [ "08", "Behavior", 3 ], [ "07", "Interaction", 2 ], [ "10", "Interaction Similarity", 2 ], [ "15", "Comparative Interaction", 2 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 1 ] ], "originating_paper": "Opportunity, Affordance, and Action Availability", "supporting_papers": [ "Opportunity, Affordance, and Action Availability", "Representation, Invariance, and Projection", "Formal Models of Computational Interaction", "Foundations of Computational Interaction", "Predicting Interaction" ], "aliases": [ "view", "encoding", "rendering" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "System state", "Semantic assignment" ], "dependents": [ "Representation", "Opportunity profile", "Scoped invariance" ], "contracts": [ "Projection Contract" ], "formal_mappings": [], "examples": [ "A declared mapping from a system state to a GUI, API, or auditory form." ], "counterexamples": [ "An implementation artifact with no declared target, mapping, or scope." ], "supporting_literature": [] }, { "id": "scoped-invariance", "term": "Scoped invariance", "status": "Proposed theory", "definition": "A declared property remains invariant across projections when independently specified comparison rules show that it is preserved for a stated target, observer class, context, metric, and tolerance.\n\nInvariance must be typed. Relevant types include:\n\n- ontological;\n- semantic;\n- informational;\n- structural;\n- topological;\n- computational;\n- inferential;\n- task;\n- behavioral;\n- interactional.", "boundary": "No one invariance type implies another.", "paper_hits": [], "originating_paper": "Canonical glossary", "supporting_papers": [], "aliases": [], "deprecated": [ "semantic invariance" ], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "Projection", "Equivalence" ], "dependents": [], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "interpretation", "term": "Interpretation", "status": "Proposed", "definition": "The application, recovery, construction, negotiation, or revision of semantic relations by an interpreting system under a context, competence, history, and purpose.", "boundary": "Interpretation is a process or event. Semantics specifies or stabilizes admissible relations; interpretation applies or revises them.", "paper_hits": [ [ "05", "Ontology, Semantics, Representation, and Interpretation", 47 ], [ "04", "Representation, Invariance, and Projection", 24 ], [ "01", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", 20 ], [ "09", "Measurement", 19 ], [ "16", "Foundations of Computational Interaction", 9 ], [ "07", "Interaction", 7 ], [ "06", "Opportunity, Affordance, and Action Availability", 6 ], [ "08", "Behavior", 4 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 3 ], [ "14", "Predicting Interaction", 3 ], [ "10", "Interaction Similarity", 2 ], [ "11", "Interaction Transfer", 2 ], [ "15", "Comparative Interaction", 2 ] ], "originating_paper": "Ontology, Semantics, Representation, and Interpretation", "supporting_papers": [ "Ontology, Semantics, Representation, and Interpretation", "Representation, Invariance, and Projection", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", "Measurement", "Foundations of Computational Interaction" ], "aliases": [], "deprecated": [], "observable": "No - latent/inferred", "latent": "Yes", "measurement": "Requires latent-variable model", "dependencies": [ "Representation", "Interaction history" ], "dependents": [ "Opportunity profile" ], "contracts": [], "formal_mappings": [], "examples": [ "An agent applies conventions and context to a signaled operation." ], "counterexamples": [ "Formal semantics treated as identical to a participant’s understanding." ], "supporting_literature": [] }, { "id": "interaction-participant", "term": "Interaction participant", "status": "Proposed", "definition": "Any bounded person, collective, organism, computational process, artificial system, institution, or hybrid arrangement occupying a consequential role within an interaction.\n\nA participant may observe, interpret, act, constrain, authorize, mediate, represent, store, or transform state. 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More specific terms such as human participant, computational participant, institution, observer, mediator, autonomous agent, and AI agent should be used when their additional commitments matter.", "paper_hits": [], "originating_paper": "Canonical glossary", "supporting_papers": [], "aliases": [ "participant" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [ "Agent" ], "dependents": [ "Coupling" ], "contracts": [ "Interaction Contract" ], "formal_mappings": [ "Layered observation-enriched probabilistic labeled transition system" ], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "agent", "term": "Agent", "status": "Proposed subtype", "definition": "An acting interaction participant that selects or produces actions through a policy, rule, control process, intention, or other action-selection organization.", "boundary": "Agent is not the universal term for every participant. 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R. AND ISENSEE, S. (1996) Low social psychological analysis. Behavior Research: vs. High-fidelity Prototyping Debate. ACM Inter- Methods and Instrumentation,13, (2), 210-220. actions Magazine, January, 76-85. References 501", "(1993) Human-Computer Interaction (2nd ed.). Analysis: Verbal Reports as Data. Cambridge, MA: London: Prentice-Hall Europe. The MIT Press.", "(1993) Project Ernestine: validating a GOMS J. (1993) Unpacking collaboration: the interac- analysis for predicting and explaining real-world tional organization of trading in a city dealing performance. Human-Computer Interaction, 8(3), room. In Proceedings of the Third European Con- 237-309. ference on Computer-Supported Cooperative", "1. Interview: reproduced by permission of IDEO. (1997) Tangible Bits: towards seamless interfaces, in CH1'97 Proceedings, reprinted by permission of Chapter 2 Association for Computing Machinery, Inc.", "Figure Figure 2.1 (on Color Plate 2): gif from www.ai.mit. 2.1 1 (ii) gif from www.almaden.ibm.com/cs/blueeyes/ edu/projects/medical-visionlsurgeryl reproduced by permission of IBM", "Figure 2.11 (iii): gif surgical-navigation.htm1 reproduced by permission from www.parc.xerox.com/red/members/richgold/ of Michael E. Leventon", "Figure 2.6(a): gif from livingdoc/slide6. html, reproduced by permission of http://vibes.cs.uiuc.edu/ProjectNRIVirtuelVirtueOve Rich Gold of PARC Communications", "Figure 2.12: rview.htm, reproduced by permission of Dr Daniel A. gif from www.mbay.net/-brendaWarticleslPDA. 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It must be supported through rival discrimination, diagnostic contingencies, uncertainty, and evidence appropriate to the claim.", "paper_hits": [ [ "12", "Interaction Strategies", 102 ], [ "14", "Predicting Interaction", 14 ], [ "11", "Interaction Transfer", 12 ], [ "13", "Formal Models of Computational Interaction", 10 ], [ "16", "Foundations of Computational Interaction", 8 ], [ "01", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", 6 ], [ "10", "Interaction Similarity", 6 ], [ "15", "Comparative Interaction", 5 ], [ "06", "Opportunity, Affordance, and Action Availability", 4 ], [ "08", "Behavior", 4 ], [ "09", "Measurement", 4 ], [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 2 ] ], "originating_paper": "Interaction Strategies", "supporting_papers": [ "Interaction Strategies", "Predicting Interaction", "Interaction Transfer", "Formal Models of Computational Interaction", "Foundations of Computational Interaction" ], "aliases": [], "deprecated": [], "observable": "No - latent/inferred", "latent": "Yes", "measurement": "Requires latent-variable model", "dependencies": [ "Policy", "Interaction history", "Strategy contract" ], "dependents": [], "contracts": [ "Strategy Contract" ], "formal_mappings": [ "Layered observation-enriched probabilistic labeled transition system" ], "examples": [ "An inferred pattern of conditional search, commitment, and recovery across episodes." ], "counterexamples": [ "A single successful action labeled as a strategy." ], "supporting_literature": [] }, { "id": "strategy-contract", "term": "Strategy contract", "status": "Proposed reusable artifact", "definition": "A declaration of strategy-bearing system, domain, timescale, criteria, state and observation model, state abstraction, opportunity assumptions, action repertoire, selection policy, information policy, commitments, contingency and recovery rules, switching and stopping conditions, resources, authority, identity invariants, rival strategies, uncertainty, and validity domain.", "boundary": "", "paper_hits": [ [ "12", "Interaction Strategies", 3 ] ], "originating_paper": "Interaction Strategies", "supporting_papers": [ "Interaction Strategies" ], "aliases": [], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [], "dependents": [ "Strategy" ], "contracts": [ "Strategy Contract" ], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "policy", "term": "Policy", "status": "Proposed", "definition": "A conditional relation from represented states, observations, or beliefs to action distributions.", "boundary": "A policy may be one component of a strategy. Strategy may additionally include information acquisition, commitment, resource allocation, switching, recovery, and stopping rules.", "paper_hits": [ [ "12", "Interaction Strategies", 26 ], [ "06", "Opportunity, Affordance, and Action Availability", 14 ], [ "13", "Formal Models of Computational Interaction", 12 ], [ "08", "Behavior", 10 ], [ "10", "Interaction Similarity", 7 ], [ "11", "Interaction Transfer", 6 ], [ "14", "Predicting Interaction", 6 ], [ "01", "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", 5 ], [ "05", "Ontology, Semantics, Representation, and Interpretation", 4 ], [ "07", "Interaction", 2 ], [ "09", "Measurement", 1 ], [ "16", "Foundations of Computational Interaction", 1 ] ], "originating_paper": "Interaction Strategies", "supporting_papers": [ "Interaction Strategies", "Opportunity, Affordance, and Action Availability", "Formal Models of Computational Interaction", "Behavior", "Interaction Similarity" ], "aliases": [], "deprecated": [], "observable": "No - latent/inferred", "latent": "Yes", "measurement": "Requires latent-variable model", "dependencies": [], "dependents": [ "Strategy" ], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "fundamental", "term": "Fundamental", "status": "Proposed research substrate", "definition": "A representation-independent computational substrate for declaring domain commitments, evolving system state, assigning operational semantics, and producing governed projections whose preservation, transformation, omission, introduced structure, operations, snapshots, and replay can be inspected.", "boundary": "Fundamental is not the scientific theory, a philosophical ontology, proof of CIS, or a guarantee of shared human meaning.", "paper_hits": [ [ "02", "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", 3 ], [ "03", "How Sciences Define Their Objects", 1 ], [ "04", "Representation, Invariance, and Projection", 1 ], [ "14", "Predicting Interaction", 1 ] ], "originating_paper": "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", "supporting_papers": [ "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", "How Sciences Define Their Objects", "Representation, Invariance, and Projection", "Predicting Interaction" ], "aliases": [], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [], "dependents": [], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] }, { "id": "computational-interaction-science", "term": "Foundations of Computational Interaction", "status": "Proposed research program; disciplinary autonomy unproven", "definition": "A research program that studies interaction as an explanatory target by separating and comparing declared domain commitments, state, semantics, projection, representation, interpretation, opportunity, coupling, behavior, measurement, similarity, strategy, and evidence.\n\nCIS must justify itself through comparative explanatory gain, empirical validity, reproducible methods, and error-sensitive predictions. It does not replace HCI, psychology, anthropology, cognitive science, design, computer science, or related disciplines.", "boundary": "", "paper_hits": [ [ "16", "Foundations of Computational Interaction", 5 ], [ "14", "Predicting Interaction", 1 ] ], "originating_paper": "Foundations of Computational Interaction", "supporting_papers": [ "Foundations of Computational Interaction", "Predicting Interaction" ], "aliases": [ "Computational Interaction" ], "deprecated": [], "observable": "Conditional on observation model", "latent": "No or not inherently", "measurement": "Measure only under declared operationalization", "dependencies": [], "dependents": [ "Interaction" ], "contracts": [], "formal_mappings": [], "examples": [], "counterexamples": [], "supporting_literature": [] } ] ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Source_Data/papers.json (1191 lines, 76.2 KiB) ======================================================================== [ { "id": "01", "folder": "01_Scientific_Explanandum", "title": "INTERACTION AS A\nSCIENTIFIC EXPLANANDUM", "docx": "02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.docx", "pdf": "02_Research_Papers/01_Scientific_Explanandum/Interaction_as_a_Scientific_Explanandum.pdf", "mds": [], "headings": [ "Contents", "Executive decision", "Recommended institutional form", "Minimum theoretical contribution", "1. Research question and decision standard", "1.1 Discipline-necessity tests", "1.2 Existing labels do not establish an autonomous discipline", "2. Scope and core explanandum", "2.1 Scope", "2.2 Working definition of interaction", "2.3 Explanatory target", "3. Method and evidential basis", "4. Literature review and explanatory boundaries", "4.1 Boundary matrix", "4.2 What the literature collectively explains", "4.3 Where the literature collectively stops", "4.3.1 Cross-timescale integration", "4.3.2 Typed representation equivalence", "4.3.3 Context-conditioned behavioral evidence", "4.3.4 Cross-scale predictive comparison", "5. Critique of the current working direction", "5.1 \"Interaction behavior develops through accumulated experience interacting with information systems\"", "5.2 \"Previous interaction experiences influence future interaction\"", "5.3 \"Interaction cannot be fully understood from interface events alone\"", "5.4 \"Behavior should be interpreted relative to the information, actions, and constraints available at the time\"", "5.5 \"Semantic understanding may exist independently of visual representation\"", "5.6 \"Visual structure may influence interaction before semantic understanding is fully formed\"", "5.7 \"Interaction may be describable through a stable set of primitives independent of specific software\"", "6. Recommended terminology", "6.1 Candidate-term disposition", "6.2 Terms that should not be introduced", "7. Canonical ontology", "7.1 Entities and relations", "7.2 Typed equivalence relations", "7.3 Interaction similarity profile", "8. Foundational assumptions", "9. First principles", "10. Relationships among concepts", "10.1 Core causal cycle", "10.2 Dependency graph", "11. Minimum formal model", "11.1 Why this is not a new theory by itself", "12. Smallest meaningful unit of interaction", "13. What constitutes evidence in interaction research", "13.1 Observation is not evidence by itself", "13.2 Context-complete interaction record", "13.3 Evidence hierarchy by claim type", "14. Universals, acquisitions, and population variation", "14.1 Plausible near-universal constraints", "14.2 Primarily acquired components", "14.3 Demographic variables", "15. Learning, adaptation, and transfer", "15.1 Required distinctions", "15.2 Transfer definition", "15.3 Mechanistic predictions", "16. Representation, meaning, and visual structure", "16.1 Representation-content-interpretation triad", "16.2 Visual structure", "17. Falsifiability and decisive tests", "17.1 Claim-level falsification tests", "17.2 Evidence that a new discipline is unnecessary", "17.3 Evidence that could justify a new discipline", "17.4 Recommended decisive benchmark", "18. Recommended sequence for foundational papers", "Paper 1 - The discipline-necessity argument", "Paper 2 - Canonical ontology and terminology", "Paper 3 - Context-complete interaction evidence", "Paper 4 - Interaction history as mediated learned state", "Paper 5 - Typed equivalence and transfer", "Paper 6 - Coupled multi-timescale interaction model", "Paper 7 - Social and institutional extension", "Paper 8 - The decisive comparative test", "19. Formal argument", "19.1 Argument against creating an independent discipline now", "19.2 Strongest counterargument", "19.3 Response", "20. Final conclusion", "21. Limitations", "References" ], "refs": [ "Ashby, W. R. (1956). An introduction to cybernetics. Chapman & Hall.", "Bahr, G. S., & Stary, C. (2016). 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Cognitive Science, 18(1), 87-122.", "End of report" ], "figure_captions": [ "Figure 1. Dependency graph for the minimum ontology. Arrows indicate explanatory dependence, not necessarily temporal precedence." ], "embedded_media": 1, "tables": 8 }, { "id": "02", "folder": "02_Primary_Scientific_Object", "title": "CAN INTERACTION BECOME A\nPRIMARY SCIENTIFIC OBJECT?", "docx": "02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.docx", "pdf": "02_Research_Papers/02_Primary_Scientific_Object/Can_Interaction_Become_a_Primary_Scientific_Object.pdf", "mds": [], "headings": [ "Abstract", "1. Introduction", "2. What Constitutes a Scientific Object?", "3. How Existing Sciences Define Their Objects", "4. How Interaction Is Currently Treated", "4.1 Competing ontological roles", "4.2 Philosophical assumptions", "5. Systematic Literature Review", "5.1 Review design", "5.2 Major formalization traditions", "6. Comparative Analysis", "6.1 Does interaction have identity conditions?", "6.2 Can interaction-level properties be non-reducible?", "6.3 Criteria assessment", "7. Arguments Supporting Interaction as a Scientific Object", "8. Arguments Against", "9. Attempted Falsification: Are Existing Theories Already Complete?", "10. Minimum Ontology if Interaction Is the Focal Object", "11. Minimum Formal Object", "12. Required Empirical Program", "13. Threats to Validity", "14. Discussion", "15. Conclusion", "References" ], "refs": [ "Abramsky, S. (2013). Semantics of interaction. arXiv:1312.0121.", "American Chemical Society. (2026). Chemistry is everywhere: What is chemistry?", "American Psychological Association. (n.d.). Psychology. APA Dictionary of Psychology.", "Ashby, W. R. (1956). An introduction to cybernetics. Chapman & Hall.", "Bertalanffy, L. von. (1968). General system theory: Foundations, development, applications. George Braziller.", "Borko, H. (1968). 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The prospects for psychological science in human-computer interaction. Human-Computer Interaction, 1(3), 209-242.", "Norman, D. A. (2013). The design of everyday things (Rev. ed.). Basic Books.", "Oulasvirta, A., Jokinen, J. P. P., & Howes, A. (2022). Computational rationality as a theory of interaction. Proceedings of CHI 2022. ACM. https://doi.org/10.1145/3491102.3517739", "Oulasvirta, A., Kristensson, P. O., Bi, X., & Howes, A. (Eds.). (2018). Computational interaction. Oxford University Press.", "Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man, and Cybernetics - Part A, 30(3), 286-297.", "Reeves, S. (2015). Human-computer interaction as science. Proceedings of the Fifth Decennial Aarhus Conference, 73-84.", "Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696-735.", "Simon, H. A. (1962). The architecture of complexity. Proceedings of the American Philosophical Society, 106(6), 467-482.", "Suchman, L. A. (1987). Plans and situated actions: The problem of human-machine communication. Cambridge University Press.", "Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. MIT Press.", "Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind. MIT Press.", "Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM, 40(5), 80-91.", "Wiener, N. (1948). Cybernetics: Or control and communication in the animal and the machine. Wiley.", "Winograd, T., & Flores, F. (1986). Understanding computers and cognition. Ablex.", "Zhang, J., & Norman, D. A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18(1), 87-122." ], "figure_captions": [ "Table 1 compares scientific structure rather than disciplinary history. “Observer” identifies the investigator or measurement system; “observed” identifies the focal target. The rows are ideal types: each discipline contains internal disagreement and subfields that cross the stated boundary." ], "embedded_media": 0, "tables": 5 }, { "id": "03", "folder": "03_Architecture_of_Sciences", "title": "How Sciences Define Their Objects", "docx": "02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.docx", "pdf": "02_Research_Papers/03_Architecture_of_Sciences/How_Sciences_Define_Their_Objects.pdf", "mds": [], "headings": [ "Abstract", "Introduction", "Problem Statement", "Current Theories of Scientific Organization", "Logical structure and explanatory relations", "Paradigms, research programs, and disciplinary matrices", "Experimental objects and epistemic things", "Natural kinds, classifications, and constructed targets", "Levels, mechanisms, and perspectival organization", "Communities, boundaries, and institutional emergence", "Comparative Survey of Mature Disciplines", "Recurring Architectural Structures", "Counterexamples", "Method-centered fields", "Historical sciences", "Interpretive and reflexive sciences", "Formal and design sciences", "Fields without a single paradigm", "Proposed General Architecture", "Definitions", "Relations among components", "Necessary and non-necessary components", "Application to Interaction as a Worked Example", "Threats to Validity", "Discussion", "Conclusion", "References", "Appendix A: Evaluation Criteria for a Candidate Scientific Object" ], "refs": [ "Abbott, A. (2001). Chaos of disciplines. University of Chicago Press.", "Bertalanffy, L. von. (1968). General system theory. George Braziller.", "Boyd, R. (1991). Realism, anti-foundationalism and the enthusiasm for natural kinds. Philosophical Studies, 61, 127-148.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The psychology of human-computer interaction. Erlbaum.", "Cartwright, N. (1983). How the laws of physics lie. Oxford University Press.", "Cartwright, N. (1989). Nature's capacities and their measurement. Oxford University Press.", "Craver, C. F. (2007). Explaining the brain. Oxford University Press.", "Daston, L. (Ed.). (2000). Biographies of scientific objects. University of Chicago Press.", "Daston, L., & Galison, P. (2007). Objectivity. Zone Books.", "Dupré, J. (1993). The disorder of things. Harvard University Press.", "Fleck, L. (1979). Genesis and development of a scientific fact (original work published 1935). University of Chicago Press.", "Gibson, J. J. (1979). 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Thinking about mechanisms. Philosophy of Science, 67, 1-25.", "Marr, D. (1982). Vision. W. H. Freeman.", "Mayr, E. (1982). The growth of biological thought. Harvard University Press.", "Newell, A., & Simon, H. A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19, 113-126.", "Norman, D. A. (2013). The design of everyday things (rev. ed.). Basic Books.", "Pearl, J. (2000). Causality. Cambridge University Press.", "Popper, K. R. (1959). The logic of scientific discovery. Hutchinson.", "Rheinberger, H.-J. (1997). Toward a history of epistemic things. Stanford University Press.", "Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton University Press.", "Simon, H. A. (1996). The sciences of the artificial (3rd ed.). MIT Press.", "Stichweh, R. (1992). The sociology of scientific disciplines. Science in Context, 5, 3-15.", "Suchman, L. A. (1987). Plans and situated actions. Cambridge University Press.", "Wiener, N. (1948). Cybernetics. MIT Press.", "Wimsatt, W. C. (2007). Re-engineering philosophy for limited beings. Harvard University Press.", "Woodward, J. (2003). Making things happen. Oxford University Press." ], "figure_captions": [ "Table 1 records dominant structures rather than exhaustive internal diversity. 'Observer' identifies the epistemic role that selects and records evidence, not necessarily a person external to the system. 'Mechanism/dependency' includes lawful, causal, structural, functional, historical, computational, interpretive, and statistical forms." ], "embedded_media": 0, "tables": 6 }, { "id": "04", "folder": "04_Representation_and_Projection", "title": "Representation, Invariance, and Projection", "docx": "02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.docx", "pdf": "02_Research_Papers/04_Representation_and_Projection/Representation_Invariance_and_Projection.pdf", "mds": [ "02_Research_Papers/04_Representation_and_Projection/Scoped_Invariance_Under_Projection_v0.4.md" ], "headings": [ "Abstract", "1. Problem Statement", "2. Literature Review Method", "3. Major Theories of Representation", "3.1 Semiotic and referential accounts", "3.2 Philosophy of science and scientific modeling", "3.3 Mental, external, and distributed representation", "3.4 Mathematics, logic, and model theory", "3.5 Information theory and coding", "3.6 Cartography and information visualization", "3.7 Programming languages, compilers, and computation", "3.8 Databases, views, and bidirectional transformations", "3.9 Knowledge representation", "3.10 Accessibility, multimodality, and HCI", "4. Representation-Target Relations", "5. Preservation, Transformation, and Loss", "6. Typed Equivalence Relations", "7. Invariance Under Projection", "8. Epistemic Access and Opportunity", "9. Comparative Cases", "9.1 One semantic structure as table, graph, map, and narrative", "9.2 One scientific target through equations, diagrams, simulation, and prose", "9.3 One computational system through GUI, CLI, API, and conversation", "9.4 Accessibility across visual, auditory, and tactile forms", "9.5 Informational equivalence with different reasoning", "10. Candidate Formal Model", "11. Falsification Tests", "12. Threats to Validity", "13. Implications for Interaction Research", "14. Conclusion", "15. Reusable Representation-Analysis Framework", "A. Representation Taxonomy", "B. Equivalence Matrix", "C. Projection Contract", "D. Representation Comparison Protocol", "E. Falsification Matrix", "16. References" ], "refs": [ "Blackwell, A. F., Britton, C., Cox, A., Green, T. R. G., Gurr, C., Kadoda, G., Kutar, M., Loomes, M., Nehaniv, C., Petre, M., Roast, C., Roes, C., Wong, A., & Young, R. M. (2001). Cognitive dimensions of notations: Design tools for cognitive technology. 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Comparative Case Studies", "8.1 Mathematical theorem", "8.2 Transportation network", "8.3 Computational workflow", "9. Counterarguments and Falsification", "10. Threats to Validity", "11. Discussion", "12. Conclusion", "13. Required Artifacts", "A. Canonical Definitions", "B. Relationship Diagram", "C. Transformation Matrix", "D. Cross-Disciplinary Vocabulary", "E. Open Problems", "References" ], "refs": [ "Bar-Hillel, Y., & Carnap, R. (1953). Semantic information. British Journal for the Philosophy of Science, 4, 147-157.", "Borst, W. N. (1997). Construction of Engineering Ontologies for Knowledge Sharing and Reuse. University of Twente.", "Dretske, F. I. (1981). Knowledge and the Flow of Information. MIT Press.", "Floridi, L. (2004). Outline of a theory of strongly semantic information. Minds and Machines, 14, 197-221.", "Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.", "Grice, H. P. (1957). Meaning. 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Its rule is that invariance must be typed and tested independently for ontology, formal semantics, information, representation, interpretation, and behavior." ], "embedded_media": 0, "tables": 9 }, { "id": "06", "folder": "06_Opportunity", "title": "Opportunity, Affordance, and Action Availability", "docx": "02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.docx", "pdf": "02_Research_Papers/06_Opportunity/Opportunity_Affordance_and_Action_Availability.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Literature Review Method", "3. Affordance Traditions", "4. Action-Set and Choice-Set Traditions", "5. Capability, Permission, and Reachability", "6. Discoverability, Signaling, and Belief", "7. Candidate Typed Opportunity Model", "8. Formal Representations", "9. Empirical Measurement", "10. Comparative Cases", "11. Operationalized Hypotheses", "H1 — Signaling effect", "H2 — Belief mediation", "H3 — Opportunity inequivalence", "H4 — Training effect", "H5 — Recovery effect", "H6 — Opportunity model gain", "12. Falsification Tests", "13. Threats to Validity", "14. Implications for Interaction Research", "15. Conclusion", "16. Reusable Artifacts", "A. Canonical Vocabulary", "B. Opportunity Matrix", "C. Opportunity Contract", "D. Opportunity Comparison Protocol", "E. Evidence Map", "17. References" ], "refs": [ "Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.", "Norman, D. A. (1988/2013). The Design of Everyday Things. Basic Books.", "Gaver, W. W. (1991). Technology affordances. Proceedings of CHI ’91, 79–84.", "Hartson, H. R. (2003). Cognitive, physical, sensory, and functional affordances in interaction design. Behaviour & Information Technology, 22(5), 315–338.", "Stoffregen, T. A. (2003). Affordances as properties of the animal–environment system. 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Falsification and Rival Accounts", "17. Threats to Validity", "18. Implications for Computational Interaction Research", "19. Conclusion", "20. Reusable Artifacts", "20.1 Canonical vocabulary", "20.2 Minimal annotation schema", "20.3 Behavioral comparison protocol", "21. References" ], "refs": [ "Beer, R. D. (1995). A dynamical systems perspective on agent-environment interaction. Artificial Intelligence, 72, 173-215.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Lawrence Erlbaum.", "Davidson, D. (1980). Essays on Actions and Events. Oxford University Press.", "Dewey, J. (1896). The reflex arc concept in psychology. Psychological Review, 3, 357-370.", "Engestrom, Y. (1987). Learning by Expanding. Orienta-Konsultit.", "Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.", "Hutchins, E. (1995). Cognition in the Wild. MIT Press.", "Kahneman, D., & Tversky, A. (1979). 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Evidence Taxonomy", "14. Falsification Tests", "15. Threats to Validity", "16. Implications for Interaction Research", "17. Conclusion", "18. Reusable Artifacts", "A. Measurement Ontology", "B. Canonical Metric Registry", "C. Evidence Taxonomy", "D. Construct Card", "E. Measurement Contract", "F. Uncertainty Budget Template", "G. Experimental Protocol", "19. References" ], "refs": [ "Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103(2684), 677-680.", "Suppes, P., & Zinnes, J. L. (1963). Basic measurement theory. In Handbook of Mathematical Psychology, Vol. 1.", "Krantz, D. H., Luce, R. D., Suppes, P., & Tversky, A. (1971). Foundations of Measurement, Volume I. Academic Press.", "Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302.", "Messick, S. (1995). Validity of psychological assessment. American Psychologist, 50(9), 741-749.", "Campbell, D. T., & Fiske, D. W. (1959). 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Science, 349(6251)." ], "figure_captions": [], "embedded_media": 0, "tables": 4 }, { "id": "10", "folder": "10_Similarity", "title": "Interaction Similarity", "docx": "02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.docx", "pdf": "02_Research_Papers/10_Similarity/Interaction_Similarity_Toward_a_General_Theory_of_Comparable_Interactions.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Method", "3. Why Similarity Is Not One Relation", "4. Canonical Distinctions", "5. Similarity Ontology", "6. Typed Dimensions of Interaction Comparison", "7. Equivalence Hierarchy", "8. Formal Comparison Contract", "9. Evidence and Measurement Requirements", "10. Comparative Cases", "11. Admissible Transformations", "12. Comparison Protocol", "13. Falsification Tests", "14. Threats to Validity", "15. Implications for Interaction Research", "16. Conclusion", "17. Reusable Artifacts", "A. Similarity Ontology", "B. Similarity Taxonomy", "C. Interaction Equivalence Hierarchy", "D. Similarity Contract", "E. Similarity Comparison Protocol", "F. Admissible Transformation Matrix", "G. Falsification Matrix", "18. References" ], "refs": [ "Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327-352.", "Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science, 237, 1317-1323.", "Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady, 10, 707-710.", "Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49.", "Sanfeliu, A., & Fu, K. S. (1983). A distance measure between attributed relational graphs for pattern recognition. IEEE Transactions on Systems, Man, and Cybernetics, 13(3), 353-362.", "Bunke, H. (1997). On a relation between graph edit distance and maximum common subgraph. Pattern Recognition Letters, 18, 689-694.", "Milner, R. (1989). Communication and Concurrency. Prentice Hall.", "van Glabbeek, R. J. (1990). The linear time-branching time spectrum. In CONCUR 1990. Springer.", "Park, D. (1981). Concurrency and automata on infinite sequences. In Theoretical Computer Science. Springer.", "Lange, M., Lozes, E., & Vargas Guzman, M. (2013). Model-checking process equivalences. Theoretical Computer Science, 560, 326-347.", "Abate, A., Bacci, G., Bacci, G., & Larsen, K. G. (2017). On the relationship between bisimulation and trace equivalence in an approximate probabilistic context.", "van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action (2nd ed.). Springer.", "Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions.", "García-Bañuelos, L., van Beest, N. R. T. P., Dumas, M., La Rosa, M., & Mertens, W. (2018). Complete and interpretable conformance checking of business processes. IEEE Transactions on Software Engineering, 44(3), 262-290.", "Suppes, P., Krantz, D. H., Luce, R. D., & Tversky, A. (1989). Foundations of Measurement, Vol. II. Academic Press.", "Kruskal, J. B., & Wish, M. (1978). Multidimensional Scaling. Sage.", "Gower, J. C. (1971). A general coefficient of similarity and some of its properties. Biometrics, 27, 857-871.", "Rosenbaum, P. R. (2020). Design of Observational Studies (2nd ed.). Springer.", "ISO 9241-11:2018. Ergonomics of human-system interaction - Usability: Definitions and concepts.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum.", "Hutchins, E. (1995). Cognition in the Wild. MIT Press.", "Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press." ], "figure_captions": [], "embedded_media": 0, "tables": 5 }, { "id": "11", "folder": "11_Transfer", "title": "Interaction Transfer", "docx": "02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.docx", "pdf": "02_Research_Papers/11_Transfer/Interaction_Transfer_Toward_a_Theory_of_Experience_and_Adaptation.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Method and Scope", "3. Existing Theories of Transfer", "3.1 Common elements and structural overlap", "3.2 Abstraction, schema, and analogy", "3.3 Skill acquisition and procedural knowledge", "3.4 Expertise", "3.5 Reinforcement learning and transfer learning", "3.6 Situated, activity, and distributed accounts", "4. Canonical Distinctions", "5. What Transfers?", "6. Interaction Experience Model", "7. Candidate Adaptation Model", "8. Formal Definition", "9. Transfer Taxonomy", "10. Comparative Cases", "10.1 Interface migration", "10.2 Modality migration", "10.3 Cross-device interaction", "10.4 Software families", "10.5 Expert and novice", "10.6 Repeated task performance", "11. Measurement and Metrics", "12. Transfer Protocol", "13. Falsification Matrix", "14. Threats to Validity", "15. Reusable Artifacts", "A. Transfer Ontology", "B. Transfer Contract", "C. Experience Model", "D. Metric Registry", "16. Conclusion", "17. References" ], "refs": [ "Thorndike, E. L., & Woodworth, R. S. (1901). The influence of improvement in one mental function upon the efficiency of other functions. Psychological Review.", "Judd, C. H. (1908). The relation of special training to general intelligence. Educational Review.", "Singley, M. K., & Anderson, J. R. (1989). The Transfer of Cognitive Skill. Harvard University Press.", "Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128(4), 612-637.", "Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How People Learn. National Academies Press.", "National Academies of Sciences, Engineering, and Medicine. (2018). How People Learn II. National Academies Press.", "Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155-170.", "Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1-38.", "Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-406.", "Fitts, P. M., & Posner, M. I. (1967). Human Performance. Brooks/Cole.", "Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406.", "Lave, J. (1988). Cognition in Practice. Cambridge University Press.", "Greeno, J. G., Smith, D. R., & Moore, J. L. (1993). Transfer of situated learning. In Transfer on Trial.", "Beach, K. (1999). Consequential transitions: A sociocultural expedition beyond transfer in education. Review of Research in Education, 24, 101-139.", "Hutchins, E. (1995). Cognition in the Wild. MIT Press.", "Engestrom, Y. (1987). Learning by Expanding. Orienta-Konsultit.", "Sutton, R. S., Precup, D., & Singh, S. (1999). Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211.", "Taylor, M. E., & Stone, P. (2009). Transfer learning for reinforcement learning domains: A survey. Journal of Machine Learning Research, 10, 1633-1685.", "Pan, S. J., & Yang, Q. (2010). A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359.", "Thorndike, R. L. (1949). Personnel Selection: Test and Measurement Techniques. Wiley.", "Norman, D. A. (2013). The Design of Everyday Things. Basic Books.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum.", "Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press." ], "figure_captions": [], "embedded_media": 0, "tables": 3 }, { "id": "12", "folder": "12_Strategies", "title": "Interaction Strategies", "docx": "02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.docx", "pdf": "02_Research_Papers/12_Strategies/Interaction_Strategies_Toward_a_Theory_of_Behavioral_Organization.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Review Method", "3. Existing Traditions", "4. Canonical Distinctions", "5. Canonical Definition", "6. Strategy Ontology", "7. Strategy Taxonomy", "8. Policy Representation", "9. Strategy Grammar and Composition", "10. Strategy Lifecycle", "11. Inferring Strategies", "12. Strategy Evidence Hierarchy", "13. Comparative Cases", "14. Strategy, Transfer, and Learning", "15. Falsification and Rival Accounts", "16. Threats to Validity", "17. Implications for Interaction Research", "18. Conclusion", "19. Reusable Artifacts", "A. Strategy Ontology", "B. Strategy Taxonomy", "C. Strategy Contract", "D. Strategy Inference Protocol", "E. Strategy Evidence Hierarchy", "20. References" ], "refs": [ "Bratman, M. E. (1987). Intention, Plans, and Practical Reason. Harvard University Press.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum.", "Cohen, P. R., & Levesque, H. J. (1990). Intention is choice with commitment. Artificial Intelligence, 42(2-3), 213-261.", "Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451-482.", "Hutchins, E. (1995). Cognition in the Wild. MIT Press.", "Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101, 99-134.", "Newell, A., & Simon, H. A. (1972). Human Problem Solving. Prentice-Hall.", "Norman, D. A. (1986). Cognitive engineering. In D. A. Norman & S. W. Draper (Eds.), User Centered System Design. Erlbaum.", "Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99-118.", "Suchman, L. A. (1987). Plans and Situated Actions. Cambridge University Press.", "Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press.", "Sutton, R. S., Precup, D., & Singh, S. (1999). Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211.", "Bacon, P.-L., Harb, J., & Precup, D. (2017). The option-critic architecture. Proceedings of AAAI.", "Fikes, R. E., & Nilsson, N. J. (1971). STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2, 189-208.", "Rao, A. S., & Georgeff, M. P. (1995). BDI agents: From theory to practice. Proceedings of ICMAS.", "Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. Knowledge Engineering Review, 10(2), 115-152." ], "figure_captions": [], "embedded_media": 0, "tables": 3 }, { "id": "13", "folder": "13_Formal_Models", "title": "Formal Models of Computational Interaction", "docx": "02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.docx", "pdf": "02_Research_Papers/13_Formal_Models/Formal_Models_of_Computational_Interaction_Toward_a_Mathematical_Foundation.pdf", "mds": [ "02_Research_Papers/13_Formal_Models/The_Limits_of_Computational_Interaction_Models_v0.2.md" ], "headings": [ "Abstract", "1. Problem Statement", "2. Evaluation Method", "3. Formal Obligations Derived from the Theory", "4. Labeled Transition Systems", "5. Petri Nets and Workflow Nets", "6. Process Algebras", "7. Statecharts", "8. Event Structures", "9. MDPs and POMDPs", "10. Category-Theoretic Process Models", "11. Multi-Agent and Game-Based Models", "12. Comparative Result", "13. Recommended Formal Foundation", "14. Formal Semantics", "15. Analyzability and Empirical Suitability", "16. Falsification and Threats to Validity", "17. Conclusion", "18. Reusable Artifacts", "A. Formal Ontology Mapping", "B. Model Comparison Matrix", "C. Expressiveness Mapping", "D. Recommended Formal Profile", "19. References" ], "refs": [ "Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking. MIT Press.", "Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-580.", "Milner, R. (1980). A Calculus of Communicating Systems. Springer.", "Milner, R. (1989). Communication and Concurrency. Prentice Hall.", "Hoare, C. A. R. (1985). Communicating Sequential Processes. Prentice Hall.", "Harel, D. (1987). Statecharts: A visual formalism for complex systems. Science of Computer Programming, 8, 231-274.", "Winskel, G. (1987). Event structures. In Advances in Petri Nets 1986, LNCS 255. Springer.", "van der Aalst, W. M. P. (1998). The application of Petri nets to workflow management. Journal of Circuits, Systems and Computers, 8(1), 21-66.", "van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action. Springer.", "Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press.", "Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101, 99-134.", "Fagin, R., Halpern, J. Y., Moses, Y., & Vardi, M. Y. (1995). Reasoning About Knowledge. MIT Press.", "Alur, R., Henzinger, T. A., & Kupferman, O. (2002). Alternating-time temporal logic. Journal of the ACM, 49(5), 672-713.", "Baez, J. C., & Stay, M. (2010). Physics, topology, logic and computation: A Rosetta Stone. In New Structures for Physics. Springer.", "Baez, J. C., Genovese, F., Master, J., & Shulman, M. (2021). Categories of nets. arXiv:2101.04238.", "van Glabbeek, R. J. (1990). The linear time-branching time spectrum. CONCUR 1990. Springer.", "Park, D. (1981). Concurrency and automata on infinite sequences. Theoretical Computer Science.", "Clarke, E. M., Grumberg, O., & Peled, D. A. (1999). Model Checking. MIT Press.", "Cassandras, C. G., & Lafortune, S. (2008). Introduction to Discrete Event Systems (2nd ed.). Springer.", "Reisig, W. (2013). Understanding Petri Nets. Springer." ], "figure_captions": [], "embedded_media": 0, "tables": 3 }, { "id": "14", "folder": "14_Prediction", "title": "Predicting Interaction", "docx": "02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.docx", "pdf": "02_Research_Papers/14_Prediction/Predicting_Interaction_Toward_a_Predictive_Theory_of_Computational_Interaction.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Literature Review Method", "3. Explanation, Prediction, and Intervention", "4. Prediction Ontology", "5. What Is Predictable?", "6. Predictive Traditions", "6.1 Human-performance laws", "6.2 Engineering models of interaction", "6.3 Cognitive architectures", "6.4 Bayesian and sequential models", "6.5 Machine learning", "6.6 Survival, reliability, and event-history models", "7. Candidate Predictive Framework", "8. Causal Assumptions", "9. Uncertainty and Prediction Limits", "10. Target-Specific Analysis", "10.1 Discovery", "10.2 Opportunity", "10.3 Errors", "10.4 Recovery", "10.5 Abandonment", "10.6 Adaptation", "10.7 Expertise", "10.8 Transfer", "10.9 Strategy", "11. Prediction Protocol", "12. Evaluation and Falsification", "13. Threats to Validity", "14. Implications for Foundations of Computational Interaction", "15. Conclusion", "Reusable Artifacts", "A. Prediction Contract", "B. Prediction Evidence Hierarchy", "C. Predictive Metric Registry", "D. Uncertainty Model", "E. Prediction Protocol Checklist", "F. Open Problems", "References" ], "refs": [ "Anderson, J. R. (2007). How Can the Human Mind Occur in the Physical Universe? Oxford University Press.", "Angelopoulos, A. N., & Bates, S. (2021). A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification. arXiv:2107.07511.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum.", "Card, S. K. (1986). The Model Human Processor: A Model for Making Engineering Calculations of Human Performance. Proceedings of the Human Factors Society.", "Fitts, P. M. (1954). The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement. Journal of Experimental Psychology, 47(6), 381-391.", "Hick, W. E. (1952). On the Rate of Gain of Information. Quarterly Journal of Experimental Psychology, 4(1), 11-26.", "Hyman, R. (1953). Stimulus Information as a Determinant of Reaction Time. Journal of Experimental Psychology, 45(3), 188-196.", "Jastrzembski, T. S., & Charness, N. (2007). The Model Human Processor and the Older Adult: Parameter Estimation and Validation Within a Mobile Phone Task. Journal of Experimental Psychology: Applied, 13(4), 224-248.", "Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and Acting in Partially Observable Stochastic Domains. Artificial Intelligence, 101, 99-134.", "Lei, J., G'Sell, M., Rinaldo, A., Tibshirani, R. J., & Wasserman, L. (2018). Distribution-Free Predictive Inference for Regression. Journal of the American Statistical Association, 113(523), 1094-1111.", "Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press.", "Pearl, J. (2012). The Do-Calculus Revisited. Proceedings of UAI.", "Shmueli, G. (2010). To Explain or to Predict? Statistical Science, 25(3), 289-310.", "Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press.", "Yarkoni, T., & Westfall, J. (2017). Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning. Perspectives on Psychological Science, 12(6), 1100-1122.", "Earlier papers in the Computational Interaction research program: Interaction; Behavior; Measurement; Representation, Invariance, and Projection; Opportunity, Affordance, and Action Availability; Interaction Similarity; Interaction Transfer; Interaction Strategies; Formal Models of Computational Interaction." ], "figure_captions": [], "embedded_media": 0, "tables": 9 }, { "id": "15", "folder": "15_Comparative_Interaction", "title": "Comparative Interaction", "docx": "02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.docx", "pdf": "02_Research_Papers/15_Comparative_Interaction/Comparative_Interaction_Toward_a_Scientific_Method_for_Comparing_Computational_Interactions.pdf", "mds": [], "headings": [ "Abstract", "1. Problem Statement", "2. Foundations Inherited from the Research Program", "3. Literature Foundations", "3.1 Formal equivalence and conformance", "3.2 Measurement and context of use", "3.3 Accessibility and non-compensatory requirements", "3.4 Multi-criteria decision analysis", "4. Comparison Ontology", "5. Interaction Comparison Taxonomy", "6. Admissibility Gates", "7. Comparison Relations", "8. Comparative Evaluation Framework", "9. Interaction Scorecard", "10. Comparison Protocol", "11. Admissible Comparison Rules", "12. Comparative Cases", "12.1 GUI and command line over the same operation set", "12.2 API and conversational interface", "12.3 Accessibility variants", "12.4 Novice and expert use", "12.5 Simulated and observed interaction", "13. Statistical and Formal Analysis", "14. Decision Synthesis without Conceptual Collapse", "15. Falsification Matrix", "16. Threats to Validity", "17. Conclusion", "18. Reusable Artifact A - Comparison Contract", "19. Reusable Artifact B - Admissible Transformation Matrix", "20. Reusable Artifact C - Minimal Reporting Template", "21. References" ], "refs": [ "Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking. MIT Press.", "Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Kluwer.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Erlbaum.", "Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.", "ISO 9241-11:2018. Ergonomics of human-system interaction - Part 11: Usability: Definitions and concepts.", "JCGM 100:2008. Evaluation of measurement data - Guide to the expression of uncertainty in measurement.", "Norman, D. A. (2013). The Design of Everyday Things, revised edition. Basic Books.", "Roy, B. (1991). The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31, 49-73.", "Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions.", "van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action. Springer.", "W3C. (2023). Web Content Accessibility Guidelines (WCAG) 2.2.", "Project paper. Representation, Invariance, and Projection: A Cross-Disciplinary Theory of What Representations Preserve, Transform, and Enable.", "Project paper. Ontology, Semantics, Representation, and Interpretation: Toward a Layered Theory of Computational Meaning.", "Project paper. Opportunity, Affordance, and Action Availability: Toward a Formal Account of What an Agent Can Perceive, Believe, and Do.", "Project paper. Interaction: Toward a General Theory of Interaction.", "Project paper. Behavior: Toward a Scientific Theory of Computational Behavior.", "Project paper. Measurement: Toward a Scientific Framework for Interaction Research.", "Project paper. Interaction Similarity: Toward a General Theory of Comparable Interactions.", "Project paper. Interaction Transfer: Toward a Theory of Experience and Adaptation.", "Project paper. Interaction Strategies: Toward a Theory of Behavioral Organization.", "Project paper. Formal Models of Computational Interaction: Toward a Mathematical Foundation.", "Project paper. Predicting Interaction: Toward a Predictive Theory of Computational Interaction." ], "figure_captions": [], "embedded_media": 0, "tables": 8 }, { "id": "16", "folder": "16_Program_Synthesis", "title": "Foundations of Computational Interaction", "docx": "02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.docx", "pdf": "02_Research_Papers/16_Program_Synthesis/Computational_Interaction_Science_Foundations.pdf", "mds": [], "headings": [ "Abstract", "1. Problem and Decision Rule", "2. Method of Synthesis", "3. Explanatory Object", "4. Complete Ontology", "5. Dependency Architecture", "6. Foundational Assumptions", "7. First Principles", "8. Generative and Explanatory Mechanisms", "9. Formal Architecture", "10. Evidence and Measurement Framework", "11. Prediction", "12. Methodological Framework", "13. Empirical Program", "14. Relationship to Adjacent Sciences", "15. Explanatory Gain", "16. Final Falsification of Disciplinary Necessity", "17. Research Agenda", "18. Open Problems", "19. Canonical Vocabulary", "20. Conclusion", "References" ], "refs": [ "Ashby, W. R. (1956). An Introduction to Cybernetics.", "Baier, C., & Katoen, J.-P. (2008). Principles of Model Checking.", "Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction.", "Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7-19.", "Cousot, P., & Cousot, R. (1977). Abstract interpretation: A unified lattice model for static analysis.", "Engestrom, Y. (1987). Learning by Expanding.", "Gaver, W. W. (1991). Technology affordances. CHI '91.", "Gibson, J. J. (1979). The Ecological Approach to Visual Perception.", "Gruber, T. R. (1993). A translation approach to portable ontology specifications.", "Harel, D. (1987). Statecharts: A visual formalism for complex systems.", "Hutchins, E. (1995). Cognition in the Wild.", "ISO 9241-11:2018. Ergonomics of human-system interaction - Usability: Definitions and concepts.", "Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains.", "Norman, D. A. (2013). The Design of Everyday Things, revised edition.", "Pearl, J. (2009). Causality, 2nd ed.", "Shannon, C. E. (1948). A mathematical theory of communication.", "Suchman, L. A. (1987). Plans and Situated Actions.", "Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction, 2nd ed.", "Tinbergen, N. (1963). On aims and methods of ethology.", "Winskel, G. (1987). Event structures.", "Foundational program papers: How Sciences Define Their Objects; Can Interaction Become a Primary Scientific Object; Representation, Invariance, and Projection; Ontology, Semantics, Representation, and Interpretation; Opportunity, Affordance, and Action Availability; Interaction; Behavior; Measurement; Interaction Similarity; Interaction Transfer; Interaction Strategies; Formal Models of Computational Interaction; Predicting Interaction; Comparative Interaction." ], "figure_captions": [], "embedded_media": 0, "tables": 7 } ] ======================================================================== ## FILE: docs/90_Project/Audits/Canonical_Integration_v1.0.0/Source_Data/relations.json (338 lines, 9.3 KiB) ======================================================================== [ { "source": "domain-commitments", "target": "system-state", "source_term": "Domain commitments", "target_term": "System state", "relation": "constrains", "authority": "Canonical 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https://www.crossref.org/documentation/retrieve-metadata/rest-api/ - Crossref metadata best practices: https://www.crossref.org/documentation/principles-practices/best-practices/ - DataCite Metadata Schema: https://schema.datacite.org/ - ORCID Integration Guide: https://info.orcid.org/documentation/integration-guide/ These sources define the recommended authority-validation path. The present build validates identifier syntax, ISBN checksums, duplicates, and completeness locally. It does not claim authoritative API matching for every unresolved reference. ======================================================================== ## FILE: docs/90_Project/Audits/Editorial_Normalization_v1.1.1/Source_Data/build_summary.json (15 lines, 0.5 KiB) ======================================================================== { "counts": { "entries": 312, "with_doi": 15, "doi_valid_format": 15, "with_valid_isbn": 3, "with_volume": 53, "with_issue": 53, "with_pages": 112, "duplicate_groups": 35, "complete_core": 312 }, "source_bibliography": "/mnt/data/Computational_Interaction_Reference_Artifacts/Computational_Interaction_Science_Bibliography.bib", "source_corpus": "/mnt/data/ci_pubinfra/src/Computational_Interaction_Science_Canonical_Corpus_v1.0.0" } ======================================================================== ## FILE: docs/90_Project/Decisions/Consolidated_RC/FILE_INVENTORY.txt (179 lines, 14.2 KiB) 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90_Project/Version_2/Version_2_Research_Program.md 0208a046f6936f8fff8cb52d192a726f533e59bc6f010f8815cc21e868ee4da8 CHANGELOG.md 525a08bc096ec544482148b1f973806589e4f5758a54f2f3df1fdb57b648b840 README.md a48d61c1860c2e568a7a17acf3c19be7284fd8a87649153d714c919a57b663ec ROADMAP.md 102b8b9d7585d127ddbe86d51a93fc854d126e095644390ddad62810e4a04675 START_HERE.md 59854984853104df5c353e2f681a15fc7924742f9a2e468c29af248dce45ce03 VERSION ======================================================================== ## FILE: docs/90_Project/Negative_Results.md (79 lines, 4.5 KiB) ======================================================================== # Negative results **Status:** permanent record. Governed by [`Research_Practices.md` §4](Research_Practices.md) — entries are never deleted, never renumbered, and never rewritten into a revision note. A negative result is a hypothesis that was **held, worked on, and then disproven**. It is not a retracted draft and not a corrected error. Recording it matters because revising a claim erases the intuition behind it, and the abandoned intuition is precisely what a later reader is most likely to re-propose. Hypotheses are recorded **as they were actually held**, not softened in hindsight into something obviously wrong. --- ## N-001 — FCI vocabulary transfers directly as an application's authoring language **Hypothesis, as held.** The ontology's terms — opportunity, projection, episode, attention field, similarity contract — are the right names for the things an interactive application is *made of*. A system built on FCI would therefore adopt the vocabulary into its own types and APIs, and doing so would make the application clearer, because the names would finally match the phenomena. **Status:** falsified. **Falsified by.** The first external application to attempt it — an operational airspace-tracking system built on an independent runtime. The team adopted FCI's **architectural** commitments in full: separation of system state from representation, non-mutating projections, phase-ordered frame scheduling, and headless parity between server and client. They then **explicitly rejected the nomenclature**, in their own evaluation document, as boilerplate that would slow development without adding explanatory power — declining to rename running symbols to match the papers. **What this narrows.** FCI's value transferred as **structure, not vocabulary**. The architectural commitments survived contact with a domain that had real deadlines and real performance constraints; the naming did not. This is a meaningful narrowing of the program's claim, not a defeat — but it must be recorded as a narrowing rather than absorbed silently, because the original hypothesis was that the vocabulary *was* the contribution. **What it does not establish.** It does not show the vocabulary is wrong, only that it did not transfer *unassisted* to an application team optimizing for delivery. A single case cannot distinguish "the terms are poorly chosen" from "the terms are correct but carry a cost this team declined to pay," and the second reading is at least as likely. Distinguishing them requires either a second independent application or a study of comprehension, neither of which exists. **Reading it against §1.** The provenance here is **revealed by an independent implementation** — high independence, because the team was solving their own problem and had no stake in FCI's central question. That is stronger evidence than a fixture, and weaker than a controlled comparison. --- ## N-002 — the reference substrate demonstrates the framework's operational adequacy **Hypothesis, as held.** A deterministic C kernel that executes the ontology coherently is evidence that the framework is adequate for building real interactive systems. **Status:** falsified. **Falsified by.** The same application. Its operational requirements — network jitter absorption, client-side dead reckoning, conflict detection under partial information, and reconciliation between server-authoritative and locally-predicted state — are **entirely outside** the deterministic subset the substrate implements. The kernel's coherence says nothing about them. **What this narrows.** Passing the reference substrate's tests establishes *reference-kernel conformance* and nothing further. This was already the stated position in `app/VERSIONING.md` and the substrate README; what the application supplies is the first **external confirmation** that the disclaimer is load-bearing rather than ritual modesty. The gap it names — everything probabilistic, concurrent, and latency-bound — is the gap between the framework and an operational system. --- ## Registry discipline - Entries are numbered in the order recorded and are **permanent**. A superseded entry names its successor rather than disappearing. - An entry **reconstructed after the fact** is weaker evidence of discipline than one recorded when the belief was abandoned, and must be labelled as such. Both entries above were recorded contemporaneously with the evaluation that produced them. - A hypothesis that was never actually held does not belong here. This registry is not a list of things that would have been wrong. ======================================================================== ## FILE: docs/90_Project/Release_Notes_v1.0.md (46 lines, 4.2 KiB) ======================================================================== # CompInt Version 1.0 Release Notes **Consolidated Release Baseline** **Release Date:** July 17, 2026 **Status:** Frozen Conceptual Synthesis & Release Candidate --- ## 1. Component Version Matrix "Version 1.0" designates the consolidated release baseline of the overall Foundations of Computational Interaction conceptual corpus and research paper collection. Individual software, schema, and database sub-components carry separate version lines reflecting their independent developmental maturity: | Component | Version | Status | Description | |---|---|---|---| | **Conceptual Corpus** | 1.0.0 | Frozen | Definitional system of record: glossary, ontology, and governance contracts. | | **C Reference Substrate** | 0.1.0 | Stable (Experimental) | Bounded, freestanding C11 reference implementation and tests. | | **Contract Schemas** | 0.2.0 | Provisional Draft | 31 JSON Schemas defining the data exchange contracts. | | **Bibliography** | 1.1.2 | Normalized & Audited | Deduplicated citation library with 267 canonical entries. | | **Publication Infrastructure** | 1.0.0 | Stable | Production stylesheets and derivatives generation. | --- ## 2. Scientific Determination and Non-Claims The proposed work is framed as an **epistemic infrastructure for the scientific study of computational interaction** (specifying representation, observation, and measurement conditions), rather than a direct explanatory or predictive theory. Downstream models (explanation and prediction) are consumers of this foundation. The following constraints and boundaries are explicitly declared for Version 1.0: * **No Empirical Validation:** No study in the current repository claims empirical validation (`E` conformance). All behavioral hypotheses and causal models remain unproven and are deferred to downstream scientific models. * **Software as Apparatus:** The C reference substrate compiles and passes its test suite with pedantic checks. However, it is an experimental apparatus designed to verify internal logical coherence, not an empirical validation of human cognitive behavior. * **Computational Limits:** The C Reference Substrate is strictly bounded in capacity (maximum 16 state variables, 16 actions, 16 participants, 128 trace records, 128 reachability states, and a 16-step lookahead horizon). It disclaims probability, concurrency, causal identification, and predictive inference. * **Bibliographic Limits:** The bibliography is audited and normalized, but not fully authority-verified. An automated Crossref API check verified that 11 of 13 unique DOIs are fully valid. Two records remain unresolved: the truncated Sen & Wasow DOI (`10.1146/annurev-polisci-032015-`) and the Cambridge University Press book DOI (`10.1017/9781316272503`) which maps to the book's ISBN and resolves directly but is not indexed as a standard Crossref journal work. In accordance with the non-inference protocol, these unverified fields are left blank or noted as unresolved. --- ## 3. Historical Release Preservation Records Prior release packages are preserved byte-for-byte under `docs/90_Project/Previous_Releases/` to guarantee absolute provenance and traceability: | ZIP Filename | Size (bytes) | SHA-256 Hash | |---|---|---| | `Computational-Interaction-Science-v1.0.0.zip` | 56,614,151 | `dfaaef4bc4f84de47dc940ef71c3e94f10df3f0041138cacc2118d5c9eb93461` | | `Computational_Interaction_Science_Bibliography_Verification_v1.1.2.zip` | 472,992 | `fcd2d162c02e97a02303c09e08b6d659c7a7fda2b57382e16dd53b961405fcfe` | | `Computational_Interaction_Science_Canonical_Corpus_v1.0.0.zip` | 1,310,016 | `b121f3f78f44a1589a3090e499b54d72d0385299c2f8ee29d1a33f14ebe22002` | | `Computational_Interaction_Science_Consolidated_Release_v1.0_RC.zip` | 57,584,291 | `540ce28c8d4544b38126790d48046d3decbc4838ecb34b026c76bf84a5fd4e66` | | `Computational_Interaction_Science_Editorial_Normalization_v1.1.1.zip` | 1,540,344 | `2118ea60ea562f5a14c3e9aea0cbe5a2cabd608df0106db35e54aa7cbfd6383a` | | `Computational_Interaction_Science_Publication_Infrastructure_v1.0.0.zip` | 1,181,131 | `c6c49b1a234a1732b1caf089a9f783e9d8ce57ffcd2b4881ec7897e3e2f375eb` | | `Computational_Interaction_Science_Reference_Artifacts.zip` | 1,359,476 | `a9db6d6a2416aa1999102162c5deced10a1f1783def0fad7add347552d42dfd1` | ======================================================================== ## FILE: docs/90_Project/Repositioning_Analysis_v1.0.md (100 lines, 6.5 KiB) ======================================================================== # Editorial Repositioning Analysis **Version:** 1.0.0 **Status:** Completed Analysis and Deliverable Record **Guiding Principle:** The contribution is not an explanatory or predictive theory of computational interaction. It is an **epistemic infrastructure for the scientific study of computational interaction**, specifying the conditions under which interactions can be represented, observed, measured, compared, and modeled. --- ## 1. Reframed Scientific Motivation The opening motivation of the scholarly program is reframed from a simple disciplinary gap to a fundamental epistemological problem: > *Computational interaction currently lacks a common epistemic foundation. Without agreement on what interactions are, how they are represented, what observations are admissible, what constitutes evidence, and what measurements are valid, downstream explanations and predictions remain difficult to compare, reproduce, or accumulate.* This motivation naturally justifies the structural hierarchy of the subsequent chapters. Each component is designed to answer a necessary epistemological question to make computational interaction scientifically analyzable. --- ## 2. The 12-Chapter Epistemological Progression To establish a logical progression from baseline motivation to downstream application, the 16 existing foundational papers are reordered and consolidated into the following 12-chapter scientific program structure: | Chapter | Epistemological Question | Paper Source Mapping | Role in the Epistemic Infrastructure | |---|---|---|---| | **1. Motivation** | *Why do we need a foundation?* | Papers 1, 2, 3 | Establishes the necessity of a shared epistemic foundation for interaction. | | **2. Ontology** | *What exists?* | Paper 5 (Ontology section) | Defines foundational entities (state, action, participant) and relations. | | **3. Semantics** | *What do operations mean?* | Paper 5 (Semantics section) | Specifies transition rules, capability, and permission predicates. | | **4. Representation** | *How is it represented?* | Paper 4 (Representation section) | Formulates target state configurations and layout attributes. | | **5. Projection** | *What survives transformation?* | Paper 4 (Projection section) | Establishes structural mapping invariants, signifiers, and signals. | | **6. Interpretation** | *What is system vs. user purpose?* | Paper 5 (Interpretation section) | Separates explicit system actions from latent user intent. | | **7. Opportunity** | *What is the unit of choice?* | Paper 6 (Opportunity profile) | Establishes opportunity as a typed action-availability profile — the structure over which choice is analyzed, not a measurement unit. | | **8. Observation** | *What can be observed?* | Paper 8 (Behavioral traces) | Formulates coding rules for converting raw actions into structured traces. | | **9. Evidence** | *What counts as evidence?* | Handbooks (Experimental & Replication) | Specifies lineage verification, replication protocols, and bias checks. | | **10. Measurement** | *What can be measured?* | Paper 9 (Measurement framework) | Specifies metrics, coding invariants, and scaling parameters. | | **11. Comparison** | *What can be compared?* | Papers 10, 11, 12, 15 | Compares interactions across differing morphologies and transfer histories. | | **12. Scientific Models** | *How is it modeled?* | Papers 13, 14, 16 | Downstream consumers (Explanation & Prediction) built within the framework. | --- ## 3. Paper Contribution Dependency Map The revised dependency map explicitly separates the **Foundational Epistemic Infrastructure** from downstream **Scientific Models** (Explanation and Prediction): ```mermaid graph TD %% Program Root F[Foundations of Computational Interaction] --> Why[Why computational interaction requires scientific foundations] F --> FCI[Foundations for the scientific study of computational interaction] %% Foundational Model Layers subgraph Epistemic Infrastructure FCI --> Ont[Ontology: What exists?] FCI --> Sem[Semantics: What do operations mean?] FCI --> Rep[Representation: How is it represented?] FCI --> Proj[Projection: What survives transformation?] FCI --> Interp[Interpretation: What is system vs. user purpose?] FCI --> Opp[Opportunity: What is the unit of choice?] FCI --> Obs[Observation: What can be observed?] FCI --> Ev[Evidence: What counts as evidence?] FCI --> Meas[Measurement: What can be measured?] FCI --> Comp[Comparison: What can be compared?] end %% Downstream Consumers subgraph Downstream Scientific Models Ont --> Models[Scientific Models] Sem --> Models Rep --> Models Proj --> Models Interp --> Models Opp --> Models Obs --> Models Ev --> Models Meas --> Models Comp --> Models Models --> Expl[Explanation] Models --> Pred[Prediction] end ``` Explanation and prediction are not produced directly by the foundational model itself. Instead, they are produced by downstream scientific models built upon the shared representational, observational, and measurement framework. --- ## 4. Terminology Changes Log Precise case-sensitive replacements were executed across the Markdown corpus to ensure alignment: * **"Computational Interaction Science"** $\rightarrow$ **"Foundations of Computational Interaction"** (the scholarly program name). * The branded acronym **"CIS"** was first softened to **"the proposed model"** / **"the model"** to minimize branded improper nouns, then standardized to the defined acronym **"FCI"** (Foundations of Computational Interaction) for readability and consistency; the acronym is defined on first use in each document. * Institutional advocacy phrases (e.g., *"the model proves..."*) were replaced with scientific phrases (e.g., *"this work develops...", "the framework proposes..."*). --- ## 5. Identified Merges and Divisions * **Merge (Motivation):** Merge Papers 1, 2, and 3 into **Chapter 1: Motivation and Epistemic Need**. * **Divide (Ontology, Semantics, Interpretation):** Divide Paper 5 into three distinct chapters (**Ontology**, **Semantics**, **Interpretation**) to keep structural definition separate from operational rules and intent boundaries. * **Merge (Comparison):** Merge Papers 10, 11, 12, and 15 into **Chapter 11: Comparable Interactions and Transfer**. * **Isolate (Scientific Models):** Group Papers 13, 14, and 16 into a downstream **Chapter 12: Scientific Models**, designating them as consumer frameworks (rather than core parts of the foundational infrastructure). ======================================================================== ## FILE: docs/90_Project/Research_Practices.md (149 lines, 7.0 KiB) ======================================================================== # Research practices **Status:** active method. Governs how claims in this repository may be made, recorded, and revised. Where the corpus defines *what the program is about* and the verification gate defines *how changes are checked*, this document sits between them: it constrains **when a claim is allowed to strengthen**. The program's own stance is that its scientific necessity and empirical advantage remain to be demonstrated. That stance is only meaningful if something enforces it. These practices are that enforcement. --- ## 1. Maturity and provenance are different dimensions How settled a claim is, and what backs it, are independent. Conflating them is the most common way a research artifact overstates itself. | Provenance | Independence | |---|---| | emerged from a mechanism built earlier for another purpose | **high** | | revealed by an independent implementation or substrate | **high** | | independent adversarial test | **medium** | | fixture written against the implementation it was designed alongside | **low** | | architectural argument | **none** | Two claims can share a maturity label and differ completely in support. One exercising a mechanism that could have behaved otherwise **can fail**; one exercising a construct introduced in the same change as its test is a tautology with assertions. **Rule: maturity may never outrun provenance.** A claim cannot be called established on the strength of a check written against its own implementation. The converse is also an error — calling something a hypothesis when an independent result revealed it understates what is known. **Every unsupported claim must name the experiment that would support it.** A claim with no path to evidence is a permanent assumption wearing the costume of a pending one. --- ## 2. Preregistration Where a change is expected to establish something, record the expectation **before** doing the work, in a commit that precedes it. Commit order is the evidence; it can be checked by someone who does not trust the author. A registered prediction states what would count as **failure**, not only success. A prediction that cannot fail is a description. **Expect accuracy to fall as scope widens.** A maturing program should increasingly meet cases it did not anticipate. Accuracy rising while scope widens is a signal to scrutinize — most likely the predictions are being written to be safe. Track surprises rather than minimizing them: a program with no falsifications is not being tested. --- ## 3. The discovery criterion A **discovery** is a concept the framework was missing, found because something could not be expressed without it. Recording one requires stating: - what forced it; - why the **prior** formulation was wrong — incoherent or incomplete, not merely improvable; - **why no existing material could have revealed it**; - what was deliberately **not** generalized at the same time. The third requirement is load-bearing. It forces a discovery to demonstrate *necessity*: not "something we had not written down" but "something the prior basis could not, in principle, have exposed." Without it, any overlooked idea can be relabelled a discovery. The fourth guards the opposite failure. A change that quietly generalized three adjacent concepts looks identical to a minimal one unless the restraint is recorded. --- ## 4. Negative results are permanent A **negative result** is a hypothesis that was held, worked on, and then disproven. It is not a retracted draft and not a corrected error. Recording it matters because **revising a claim erases the intuition behind it** — and the abandoned intuition is precisely what a later reader is most likely to re-propose. The history of what a program stopped believing is often more useful than the list of what it accepted. Negative results are never deleted, never renumbered, and never rewritten into a revision note. A superseded entry names its successor rather than disappearing. Hypotheses are recorded **as they were actually held**, not softened in hindsight into something obviously wrong. An entry reconstructed after the fact is weaker evidence of discipline than one recorded when the belief was abandoned, and should be labelled as reconstructed. The registry itself is [`Negative_Results.md`](Negative_Results.md). --- ## 5. Refinements are classified before they are accepted | Kind | Meaning | Disposition | |---|---|---| | **structural** | the framework lacked a concept | accepted; becomes a recorded discovery | | **representational** | the concept existed; this expresses it better | allowed; **not** a discovery | | **convenience** | eases the work, adds no explanatory power | **not accepted** | A two-way split is insufficient: representational changes have nowhere to go and get misfiled as a neighbour. That ambiguity is how a framework drifts while appearing disciplined. Rejections should be **written down**, not merely made. A rejection count assembled from memory is a floor, not a total, and should say so. --- ## 6. Layers do not move together [`app/VERSIONING.md`](../../app/VERSIONING.md) is a research instrument, not bookkeeping. Its claim — that theory, schemas, substrate, publication infrastructure and examples version **independently** — is what prevents the most common category error in a repository like this: treating a passing test suite as evidence for a theoretical claim. - Passing C tests establishes **reference-kernel conformance only**. - A schema release does **not** imply empirical validation. - Cross-layer compatibility must be **declared in a conformance record**, never inferred from equal version numbers. Per-layer changelogs follow from this, and CI enforces them. A single shared changelog would assert exactly the coupling the policy denies. --- ## 7. What these practices do not do - They do not make the program's central thesis more likely to be true. - They do not remove author bias — where one author writes the material, registers the predictions and grades them, the record is a *discipline*, not independent evidence. Its guarantee is commit order. - They cannot establish that the framework is **useful**, only that it is being changed honestly. - They are slower than working by judgement alone. The cost is real. What it buys is the ability to say which parts of the program were forced by evidence and which were chosen. --- ## Relationship to the Fundamental engine The Fundamental engine (`fundamental-engine`) is an independent runtime that adapted substrates to a contract under a closely related protocol, and its [`docs/method/empirical-protocol.md`](https://github.com/zachshallbetter/fundamental-engine/blob/main/docs/method/empirical-protocol.md) states the domain-neutral form of this method. The two programs converged on it independently and **neither validates the other**. Fundamental is apparatus, not evidence: if the experimental platform and simulation kernel disappeared, the conceptual theory would have to remain valid. Software here is the reference implementation, not the contribution. ======================================================================== ## FILE: docs/90_Project/Reviews/Comprehensive_Repository_Review_v1.0.md (369 lines, 19.1 KiB) ======================================================================== # CompInt Version 1.0 — Comprehensive Repository Review **Artifact reviewed:** `CompInt_Version_1.0.zip` **Review date:** 2026-07-17 **Review scope:** repository architecture, authority and governance, canonical-system integration, manifests and checksums, documentation links, bibliography status, schemas and examples, C reference substrate, tests, archival preservation, and release readiness. ## Executive determination The repository is substantially improved and now has a defensible long-term structure. The conceptual corpus, research papers, external literature, reference resources, publication support, and project history are separated clearly. The C reference substrate builds cleanly and all documented tests pass. Version 1.0 is **not yet release-ready as a frozen publication artifact**. The remaining blockers are mostly integration and release-control defects rather than theoretical defects: 1. the root and internal documentation still contain stale paths and pre-refactor descriptions; 2. the machine-readable release manifest has four checksum mismatches; 3. the corpus-wide checksum file has five checksum mismatches; 4. `DOCUMENT_MAP.md` contains obsolete paths and a false statement that the research-paper corpus is absent; 5. authority rules are inconsistent across `app/AUTHORITY.md`, `docs/README.md`, and the KSR README; 6. duplicated bibliography-audit files are active in two locations; 7. the bibliography is normalized and deduplicated, but not authority-verified field by field; 8. the release contains macOS metadata and references a nonexistent `_archive/` directory. These are correctable without changing Version 1.0 theory. ## Overall assessment | Area | Assessment | Release effect | |---|---|---| | Repository architecture | Strong | Ready after documentation cleanup | | Lossless preservation | Strong | Verified structurally; historical ZIPs retained | | Canonical authority model | Mostly sound | Requires one synchronized authority statement | | Canonical registry | Present and integrated | Metadata completeness still needs review | | Research-paper organization | Strong | 16 dependency-ordered groups present | | C reference substrate | Strong within stated scope | All documented tests pass | | Schemas and examples | Strong syntactic/conformance baseline | Empirical validity remains out of scope | | Release manifest | Failing integrity checks | P0 blocker | | Corpus checksum manifest | Failing integrity checks | P0 blocker | | Documentation/path consistency | Material defects | P0/P1 blocker | | Bibliography | Useful normalized release | Not fully authority-verified | | Independent review | Not recorded | Release gate remains open | ## 1. Repository architecture The active `docs/` hierarchy is coherent: ```text docs/ ├── 01_Knowledge_System_of_Record/ ├── 02_Research_Papers/ ├── 03_External_Literature/ ├── 04_Reference/ ├── 05_Publication/ └── 90_Project/ ``` This structure correctly separates: - canonical definitions and specifications; - scholarly argument and provenance; - external literature; - reusable research resources; - publication-production material; - audits, manifests, prior releases, and Version 2 planning. The research-paper corpus is present in 16 dependency-ordered groups, from `01_Scientific_Explanandum` through `16_Program_Synthesis`. ### Finding A — `docs/README.md` is stale `docs/README.md` still describes the old structure: - `00_Project/` - `03_Research_Infrastructure/` - `04_External_Literature/` Those paths no longer match the repository. It also says source research papers remain authoritative for original arguments “until normative consolidation is ratified,” which conflicts with the stronger authority model elsewhere. **Severity:** P0 documentation-integrity defect. **Required correction:** Rewrite `docs/README.md` from the current directory tree and current authority model. ### Finding B — root `README.md` contains nonportable absolute links The root README contains five `file:///Users/...` links. These only work on one local machine. It also describes a root `_archive/` directory that is not present in the reviewed archive. **Severity:** P0 release-portability defect. **Required correction:** Replace all absolute local links with repository-relative links and remove or restore `_archive/`. ### Finding C — macOS metadata is included The ZIP contains a `__MACOSX/` tree and AppleDouble files. **Severity:** P2 packaging defect. **Required correction:** Exclude `__MACOSX`, `.DS_Store`, and `._*` files from the publication package. ## 2. Authority and governance `app/AUTHORITY.md` is the strongest authority-control document in the repository. It defines conflict resolution, supersession, deprecation, errata, and the prohibition against code silently redefining theory. ### Finding D — authority order is inconsistent across files Three different formulations currently coexist: - `app/AUTHORITY.md` places the final determination first, then glossary, ontology, schemas, and handbooks; - `app/README.md` refers to a nonexistent `docs/CANONICAL_ONTOLOGY.md` synchronization freeze; - `docs/01_Knowledge_System_of_Record/README.md` says “Ratified specifications (none yet)” outrank ontology and glossary candidates; - `docs/README.md` gives research papers residual authority pending ratification. These cannot all be controlling statements. **Severity:** P0 canonical-governance conflict. **Required correction:** Declare one authority document at repository root or make `app/AUTHORITY.md` repository-wide, then have all other files link to it without restating a divergent hierarchy. ## 3. Canonical document map `app/DOCUMENT_MAP.md` is materially stale. ### Finding E — obsolete and incorrect paths Examples include: - `docs/04_Templates/*.schema.json` - `docs/05_Dataset_Schema/interaction_study.schema.json` - `docs/EXPLAINING_COMPINT.md` The active paths are under `../docs/04_Reference/...`. ### Finding F — false corpus-absence statement The file states: > No `/research` directory is present in this checkout, so a paper-by-paper research index cannot be truthfully generated here. The reviewed package contains the complete `docs/02_Research_Papers/` hierarchy with 16 groups. This statement is obsolete and directly contradicts the current repository. **Severity:** P0 system-of-record defect. **Required correction:** Regenerate `DOCUMENT_MAP.md` from the actual tree and include every canonical artifact with current path, role, version, status, authority, dependencies, and reviewer. ## 4. Release manifests and checksums ### 4.1 `app/release-manifest.json` The manifest contains 20 artifacts. Four recorded hashes do not match current files: - `COMPINT-DET-001` — `app/README.md` - `COMPINT-DOCMAP-001` — `app/DOCUMENT_MAP.md` - `COMPINT-ONTO-SYNC-001` — canonical ontology - `COMPINT-CONTRACT-001` — common contract schema The manifest also retains known limitations that are no longer fully accurate, including “canonical concept identifiers are unratified,” while the current canonical glossary reportedly contains assigned slugs. **Severity:** P0 release-integrity failure. **Required correction:** Regenerate the manifest after all content fixes; do not hand-edit hashes. ### 4.2 `docs/90_Project/Manifests/SHA256SUMS.txt` When resolved relative to `docs/`, 259 of 264 entries match. Five files differ: - `04_Reference/Dataset_Schema/Data_Dictionary.csv` - `04_Reference/Dataset_Schema/interaction_study.schema.json` - `04_Reference/Figures/FIG-001_Concept_Dependency_Graph.pdf` - `04_Reference/Figures/FIG-001_Concept_Dependency_Graph.png` - `04_Reference/Figures/README.md` This indicates post-manifest edits or regenerated derivatives. **Severity:** P0 release-integrity failure. **Required correction:** Determine whether each changed file is intentional, preserve the source lineage, and regenerate `FILE_MANIFEST.csv` and `SHA256SUMS.txt` together. ### 4.3 Historical checksum files Checksum files inside historical audit and decision folders are relative to their original package roots, not their current extracted subdirectory. They appear broken when run in place. **Severity:** P2 usability issue, not evidence of corruption. **Required correction:** Add a short README stating the expected verification root, or preserve the original ZIP as the sole byte-verifiable historical artifact. ## 5. Canonical registry and concept system The canonical glossary and ontology exist under `08_Canonical_Registry`, and the ontology/glossary candidates remain available in their functional locations. The scientific determination is framed conservatively: CompInt is an interdisciplinary synthesis and research program, with disciplinary autonomy unproven. A search of active Markdown did not find residual claims asserting CompInt as an established independent discipline. No direct matches were found for the most obvious legacy conflations identified in the TODO. ### Finding G — registry metadata completeness remains unverified The repository establishes canonical labels and identifiers, but the review did not find machine-enforced completeness for every requested field: - maturity; - dependencies; - operationalization status; - validation status; - superseded definitions; - forbidden synonyms; - version introduced/deprecated. **Severity:** P1 release-quality issue. **Required correction:** Validate the canonical registry against an explicit schema or tabular completeness test. ### Finding H — canonical material is duplicated as views The architecture says the canonical registry is an index/view rather than a second authority. That is defensible, but it requires explicit generated-from or synchronized-with metadata. Otherwise the glossary and ontology copies can drift. **Severity:** P1 drift risk. **Required correction:** Designate one editable source per canonical concept and generate or mechanically compare the registry views. ## 6. Contracts, schemas, and examples The repository includes 31 JSON schemas and 10 identified contract instances. The test suite verifies JSON syntax, local references, study fixtures, example identities, and source/generated-output synchronization. All documented checks passed: ```text PASS: fundamental CIS substrate PASS: 8192 deterministic traces and opportunity independence PASS: identified example sources and generated output PASS: 31 JSON schemas and local references; 10 identified contract instances; valid/invalid study fixtures PASS: state projection invariant; signaling intentionally differs PASS: unsupported claim rejected; limitation recovery recorded ``` ### Finding I — tests establish syntax and internal conformance, not full semantic validity `test_schemas` is dependency-free and validates JSON syntax and local references. It does not by itself prove full JSON Schema dialect compliance, semantic consistency across all contracts, empirical validity, or interoperability with external validators. **Severity:** P1 claim-calibration issue. **Required correction:** State exactly what the tests prove. Add validation with at least one standard JSON Schema implementation before publication if schemas are normative. ### Finding J — contract ownership and compatibility metadata require review The TODO calls for stable ID, version, owner, status, schema, example, tests, and compatibility rules for each contract. The current test success does not establish that all metadata fields are complete. **Severity:** P1 closeout item. ## 7. C reference substrate The C substrate is well-bounded and accurately described as deterministic, fixed-capacity, freestanding, and experimental. It explicitly disclaims probability, concurrency, causal identification, empirical construct validation, generalized strategy inference, and stable serialization. `make test` completed successfully under C11 with `-Wall -Wextra -Wpedantic -Werror`. The freestanding object had no undefined external symbols. Stress tests covered 8,192 deterministic traces. ### Strengths - clear scope boundary; - no hidden allocation, filesystem, clock, network, or OS dependencies in the library object; - typed exhaustion behavior; - deterministic hashing/replay constraints documented; - examples tied to stable identifiers; - tests distinguish computational coherence from empirical validation. ### Finding K — naming/status inconsistency The public namespace remains `cis_`, while the program name is CompInt. This is documented as legacy compatibility, but example IDs also remain `CIS-EX-*`. The naming decision should state whether example IDs are intentionally frozen or should use a CompInt prefix in a future breaking version. **Severity:** P2 governance clarity. ### Finding L — release status is internally mixed The package is named Version 1.0, while the app manifest calls itself `internal-consolidation-candidate`, the C API is 0.1.0, schemas are 0.x drafts, and several canonical documents are 0.x provisional drafts. This can be valid under independent version lines, but the release front matter must explain that “Version 1.0” denotes the corpus release, not maturity 1.0 of every component. **Severity:** P1 release-communication issue. ## 8. Bibliography and citation integrity The bibliography package contains 267 canonical records derived from 312 source records, with 45 duplicates merged. It provides BibTeX, CSL JSON, rendered style outputs, audits, checksums, and unresolved-field reports. The bibliography checksum file passes for all 38 entries. ### Finding M — “verified” overstates authority status The metadata audit repeatedly marks DOI/ISBN fields as `syntax_valid_authority_unresolved`. At least one DOI is visibly truncated/malformed (`10.1146/annurev-polisci-032015-`). The package is therefore normalized, deduplicated, and audited, but not fully authority-verified. **Severity:** P0 if used for final publication claims; otherwise P1. **Required correction:** Rename or qualify the release as “normalized and audited” until cited records are checked against authoritative registries and publisher records. ### Finding N — active duplicate audit files Twenty-seven duplicate-hash groups exist outside historical ZIPs. Most are bibliography audits copied both to: - `docs/04_Reference/Bibliography/Verified_v1.1.2/...` - `docs/05_Publication/Bibliography_Audits/...` This reintroduces the duplication the architecture was intended to remove. **Severity:** P1 maintainability defect. **Required correction:** Keep canonical audit outputs in one location. In the other location, use a README or index linking to them. ## 9. Publication and derivative integrity The repository contains 74 PDFs and 64 DOCX files. The authority policy correctly treats these as derivatives unless explicitly designated otherwise. ### Finding O — no corpus-wide source/derivative equivalence gate The release contains many derivatives, but the active release checks do not prove that every PDF/DOCX matches its Markdown or source artifact. Existing checks cover examples and selected figures, not the entire publication corpus. **Severity:** P1 publication blocker. **Required correction:** Add a derivative-generation manifest with source ID, generator/version, generation date, and source hash. Regenerate final derivatives in one controlled release step. ## 10. Archival preservation Seven ZIP files are retained under project history, and the migration map explains their role. The active structure does not present those packages as current sources of truth. The reviewed ZIP itself passes `unzip -t` with no compressed-data errors. ### Finding P — “byte-for-byte preservation” should be tied to recorded hashes The claim is credible because original ZIPs are retained, but the release should record each archived ZIP’s size and SHA-256 in the active release manifest. **Severity:** P1 provenance strengthening. ## 11. TODO accuracy The updated TODO is materially better than the original and correctly separates Version 1 closeout from Version 2 validation. Several items marked complete based on the prior agent report must be reopened or narrowed: - `DOCUMENT_MAP.md` is not currently correct; - release-manifest metadata and hashes are not current; - corpus checksums are not fully current; - documentation paths are not synchronized; - authority statements are not consistent; - “verified bibliography” is not authority-verified; - source-to-derivative equivalence is not demonstrated corpus-wide. The TODO’s distinction between “Agent-reported” and directly inspected evidence was appropriate and prevented these claims from becoming silently authoritative. ## 12. Required closeout sequence ### P0 — must complete before calling the package Version 1.0 final 1. Choose one repository-wide authority statement and synchronize all references. 2. Rewrite root `README.md`, `docs/README.md`, KSR README, and `app/README.md` to current paths and status. 3. Regenerate `app/DOCUMENT_MAP.md` from the actual repository. 4. Resolve the five corpus checksum differences. 5. Regenerate `docs/90_Project/Manifests/FILE_MANIFEST.csv` and `SHA256SUMS.txt`. 6. Regenerate `app/release-manifest.json` and verify every hash and dependency. 7. Remove absolute `file:///` links and nonexistent `_archive/` references. 8. Qualify bibliography verification status and fix authority-verified metadata for all cited release references. 9. Re-run all tests and manifest verification after the final edits. ### P1 — publication-quality closeout 1. Remove active duplicate bibliography-audit copies. 2. Validate canonical-registry metadata completeness mechanically. 3. Validate normative schemas with a standard external JSON Schema validator. 4. Add source-to-derivative generation and equivalence records. 5. Record independent technical, methods, and ethics/community reviews. 6. Clarify component version lines in release front matter. 7. Add hashes for preserved historical ZIPs. ### P2 — cleanup 1. Exclude macOS metadata from release ZIPs. 2. Clarify future disposition of `cis_` and `CIS-EX-*` identifiers. 3. Add verification-root notes to historical checksum folders. ## Release recommendation **Decision: hold Version 1.0 final publication; approve the architecture as the release candidate baseline.** No further repository reorganization is warranted. The structure should now be frozen. Complete one controlled integration pass focused only on documentation synchronization, manifest regeneration, duplicate removal, bibliography qualification, derivative provenance, and independent review. Then generate a clean release artifact from the corrected repository and verify it from scratch. ## Evidence recorded during this review - ZIP integrity: passed. - Active files excluding macOS metadata and build outputs: 355. - Markdown files checked for relative-link existence: 85. - Broken relative Markdown links: 0. - Absolute local `file:///` links: 5. - C build and documented test suite: passed. - JSON schemas checked by project tests: 31. - Identified contract instances checked by project tests: 10. - Stress traces: 8,192. - App release-manifest artifacts: 20; checksum mismatches: 4. - Corpus manifest entries: 264; checksum mismatches: 5. - Bibliography checksum entries: 38; checksum mismatches: 0. - Duplicate content groups outside archives/build outputs: 27. ======================================================================== ## FILE: docs/90_Project/Reviews/Program_TODO_v1.0_Closeout.md (414 lines, 22.6 KiB) ======================================================================== # CompInt Program TODO — Version 1.0 Closeout and Version 2.0 Validation **Program:** Computational Interaction Science (CompInt) **Current determination:** Interdisciplinary scientific synthesis and research program **Repository baseline:** `Computational_Interaction_Science_v1.0_Lossless_Refactor` **Version 1.0 objective:** Close, verify, and publish the conceptual corpus without changing theory. **Version 2.0 objective:** Test whether CompInt constructs and contracts provide reliable, valid, causal, predictive, or intervention-relevant gain over simpler alternatives. --- ## Status legend - [ ] Not started - [~] In progress - [x] Complete - [R] Requires repository review - [!] Blocked by external dependency - [D] Decision required - [V2] Deferred to Version 2.0 research ## Priority legend - **P0** — Blocks a trustworthy Version 1.0 release - **P1** — Required for publication-quality Version 1.0 - **P2** — Required for empirical operation or external adoption - **P3** — Longer-term research expansion ## Verification evidence Status changes marked “Agent-reported” are based on the repository verification report supplied on 2026-07-17. They record reported completion but do not substitute for direct inspection of the repository, command output, manifests, or file contents. Remaining review items are limited to claims not established by that report. ## Scope rule Version 1.0 is frozen as a conceptual synthesis. Do not modify canonical definitions, ontology, contracts, or formal semantics during closeout. Any theoretical correction or extension belongs in `90_Project/Version_2/` and must not silently enter the Version 1.0 corpus. --- # A. Completed consolidation work ## A1. Scientific determination - [x] Adopt the governing determination that CompInt is an interdisciplinary scientific synthesis and research program. - [x] State that CompInt is not presently justified as an independent scientific discipline. - [x] State that future disciplinary recognition depends on comparative empirical gain. - [x] Separate current contributions from unproven claims. - [x] Verify that this determination appears consistently in every canonical Version 1.0 document. *(Agent-reported repository audit.)* - [x] Search for residual language implying established disciplinary autonomy. *(Agent-reported grep across active `/docs`; residual occurrences are framed as unproven or archived.)* ## A2. Repository architecture - [x] Refactor the repository into a single navigable structure: - `01_Knowledge_System_of_Record/` - `02_Research_Papers/` - `03_External_Literature/` - `04_Reference/` - `05_Publication/` - `90_Project/` - [x] Preserve previous releases under project history rather than mixing them with active content. - [x] Preserve provenance and historical artifacts. - [x] Generate a lossless release package. - [x] Separate repository, release, and archive concerns. - [x] Verify that every file from prior packages appears either canonically or in preserved history. *(Agent-reported; archived packages and lineage maps present.)* - [x] Confirm that no historical derivative is presented as an active source of truth. *(Agent-reported.)* ## A3. Canonical system and integration artifacts - [x] Establish the Knowledge System of Record as the sole conceptual authority. - [x] Produce canonical ontology, glossary, vocabulary, definition index, dependency graph, knowledge graph, cross-reference matrix, and artifact index. - [x] Separate research-paper provenance from canonical definitions. - [x] Isolate candidate Version 2.0 changes from Version 1.0. - [x] Confirm that the registry indexes the Knowledge System of Record rather than duplicating or redefining it. *(Agent-reported.)* - [x] Confirm one definition per canonical concept across active files. *(Agent-reported synchronization between glossary and ontology.)* ## A4. Editorial and publication infrastructure - [x] Complete an editorial-normalization pass over the available publication infrastructure. - [x] Produce editorial style, terminology, consistency, cross-reference, and readiness reports. - [x] Preserve normalized Markdown, DOCX, and PDF derivatives where available. - [x] Produce publication templates, handbooks, figure catalog, author guide, maintenance guide, and publication reports. - [R] Run the same editorial checks against the complete refactored repository, not only the earlier publication-infrastructure subset. ## A5. Bibliography - [x] Consolidate bibliography records. - [x] Produce canonical BibTeX and CSL JSON exports. - [x] Produce APA, IEEE, Chicago, and MLA renderings. - [x] Produce duplicate, missing-metadata, reference, and Crossref audit reports. - [x] Preserve unresolved metadata rather than infer it. - [x] Verify that the refactored repository points only to the latest bibliography release. *(Agent-reported path: `docs/04_Reference/Bibliography/Verified_v1.1.2/`.)* - [!] Complete authoritative field-by-field verification for all references cited in the final publication manuscript. - [!] Complete final retraction and correction checks for cited journal literature. --- # B. Version 1.0 release closeout ## P0.1 Authority and governance - [x] Create or verify `AUTHORITY.md` in the active repository. *(Agent-reported at `app/AUTHORITY.md`.)* - [x] Define the controlling order: 1. Canonical status determination. 2. Canonical glossary and ontology. 3. Normative contract specifications. 4. Research handbooks and protocols. 5. Foundational papers. 6. Formal reference specifications. 7. Reference implementations. 8. Examples and visualizations. 9. Generated derivatives. 10. Historical archives. - [x] State that code cannot silently redefine theory. - [x] State that PDF and DOCX files are derivatives unless explicitly designated otherwise. - [x] Document conflict resolution, supersession, deprecation, correction, and errata procedures. ## P0.2 Canonical document map and manifest - [x] Create or verify `DOCUMENT_MAP.md`. *(Agent-reported at `app/DOCUMENT_MAP.md`, updated for reorganized paths.)* - [x] Assign a stable document ID to every canonical artifact. *(Agent-reported.)* - [R] Record purpose, authority level, status, version, dependencies, reviewer, and canonical path. *(Paths and IDs reported complete; remaining metadata fields require manifest inspection.)* - [x] Mark every artifact as canonical, supporting, generated, historical, archived, or deprecated. *(Agent-reported through active structure and lineage maps.)* - [x] Create one machine-readable release manifest with checksums. *(Agent-reported `FILE_MANIFEST.csv` and `SHA256SUMS.txt`.)* - [x] Record source-to-derivative relationships. *(Agent-reported through `MIGRATION_MAP.md` and manifest lineage.)* - [x] Confirm that every previous release artifact is traceable. *(Agent-reported.)* ## P0.3 Canonical concept registry - [x] Confirm stable machine identifiers for every canonical concept. *(Agent-reported: 54 concepts with lowercase, hyphenated IDs.)* - [R] Require for each concept: - stable ID; - current label; - canonical definition; - status and maturity; - dependencies; - source paper; - operationalization status; - validation status; - superseded definitions; - forbidden synonyms; - version introduced; - version deprecated. - [x] Resolve any blank canonical identifier cells. *(Agent-reported.)* - [x] Confirm that legacy definitions exist only in provenance or supersession records. *(Agent-reported active/archived separation.)* - [V2] Add empirical validity and failed-validation fields as evidence accumulates. ## P0.4 Terminology consistency - [x] Verify formal name: **Computational Interaction Science**. *(Agent-reported.)* - [x] Verify short and adjectival form: **CompInt**. *(Agent-reported.)* - [x] Retain `cis_` as a documented legacy C namespace for compatibility. *(Agent-reported decision.)* - [x] Verify **Interaction Participant** as the broad canonical category where intended. *(Agent-reported.)* - [x] Verify that **Agent** is used only where action-selection organization is required. *(Agent-reported.)* - [R] Search active files for legacy semantic-state language, trace/behavior conflation, record/evidence conflation, visible/perceived opportunity conflation, and outcome/understanding equivalence. - [R] Confirm consistent symbols across papers, contracts, diagrams, and schemas. ## P0.5 Contract inventory and conformance - [R] Confirm the Version 1.0 normative contract inventory: - Projection Contract; - Opportunity Contract; - Interaction Contract; - Behavioral Evidence Contract; - Measurement Contract; - Similarity Contract; - Transfer Contract; - Strategy Contract; - Prediction Contract; - Comparison Contract. - [R] Give every contract a stable ID, version, owner, status, schema, example, validation tests, and compatibility rules. - [R] Define which contracts are required for each claim type. - [R] Create or verify `CONFORMANCE.md`. - [R] Define minimum, comparative, latent-inference, causal, and full-foundational reporting profiles. - [x] Validate all normative schemas and examples. *(Agent-reported `make test`: 31 schemas and examples pass.)* - [V2] Test whether contract fields provide measurable explanatory or predictive gain. ## P0.6 Dataset and evidence architecture - [R] Confirm modular schemas for participants, environments, contracts, raw records, coded events, traces, measures, uncertainty, similarity, transfer, strategy, prediction, and comparison. - [R] Distinguish raw records, detected events, attributed behavioral events, traces, and latent inferences. - [R] Include schema version, provenance, missingness, uncertainty, interpretation limits, and evidence lineage. - [R] Include valid and invalid examples. - [R] Confirm append-only provenance rules for corrections and deviations. - [V2] Extend schemas for continuous time, hybrid dynamics, partial order, and distributed interaction. ## P0.7 Publication editing - [R] Apply the publication style guide to the complete active corpus. - [R] Normalize American English, Oxford commas, capitalization, hyphenation, quotation style, acronym handling, defined terms, headings, and typography. - [R] Verify front matter, back matter, table of contents, lists of figures, tables, contracts, and appendices. - [R] Verify figure placement, caption style, equation numbering, glossary formatting, index formatting, page breaks, running heads, and running feet. - [R] Perform a final proof pass after typesetting. - [!] Complete tagged-PDF accessibility review and remediation. - [!] Confirm print-quality figure resolution and final export settings. ## P0.8 Bibliographic release gate - [x] Freeze citation keys for Version 1.0. *(Agent-reported.)* - [R] Confirm zero known malformed canonical records. - [x] Confirm duplicate merges and edition distinctions. *(Agent-reported: 45 duplicates merged; 267 canonical records.)* - [R] Link every correction to an authoritative source. - [R] Keep unresolved fields blank with explicit reasons. - [!] Verify cited records against Crossref, publisher records, library catalogs, ORCID, ISBN/ISSN authorities, proceedings, and standards bodies. - [!] Confirm retraction and correction status for cited works. - [R] Generate a final post-verification bibliography audit. ## P0.9 Release packaging - [x] Verify repository checksums and ZIP integrity. *(Agent-reported checksums and preserved release archives; ZIP integrity previously passed.)* - [R] Verify that generated derivatives match their canonical sources. - [R] Generate final release notes and known limitations. - [R] Produce one publication package and one preservation archive. - [x] Remove obsolete release candidates from the active working tree while retaining them in history. *(Agent-reported under `docs/90_Project/Previous_Releases/`.)* - [D] Assign final Version 1.0 publication date. - [!] Obtain ISBN or DOI only if a publisher or repository requires them. ## P0.10 Independent review - [ ] Obtain at least one independent technical review. - [ ] Obtain at least one research-methods review. - [ ] Obtain at least one ethics or community review. - [ ] Record reviewer comments, responses, accepted changes, rejected changes, and dissent. - [ ] Confirm that no review response changes Version 1.0 theory without explicit Version 2.0 governance. --- # C. Version 1.0 publication gate Version 1.0 may be released when all of the following are true: - [x] The interdisciplinary-synthesis determination is consistent across the active corpus. *(Agent-reported.)* - [x] One Knowledge System of Record governs definitions and ontology. *(Agent-reported.)* - [x] Every canonical concept has a stable ID and one active definition. *(Agent-reported: 54 concepts.)* - [ ] Every normative contract has a versioned specification and schema. - [ ] Repository authority, supersession, and versioning rules are explicit. - [x] The document map and machine-readable release manifest are complete. *(Agent-reported; metadata completeness still requires direct inspection.)* - [ ] The evidence lineage from record to claim is explicit. - [x] All normative schemas validate. *(Agent-reported `make test`.)* - [x] All included examples validate or pass their documented checks. *(Agent-reported `make test`.)* - [ ] The complete corpus has passed editorial and publication review. - [ ] The bibliography cited by the publication has completed authoritative verification. - [ ] Generated derivatives match canonical sources. - [ ] Known limitations and empirical non-claims are explicit. - [ ] Independent technical, methods, and ethics/community reviews are recorded. - [ ] No active document claims empirical or disciplinary validation beyond the evidence. --- # D. Version 2.0 empirical validation program ## P0.11 Cross-paper consistency before formal extension - [ ] Verify one definition per term across all papers. - [ ] Verify consistent equations and symbols. - [ ] Verify compatible contract fields and uncertainty models. - [ ] Verify participant and agent scopes. - [ ] Verify interaction boundaries against trace segmentation. - [ ] Verify that similarity dimensions map to measured variables. - [ ] Verify that strategy evidence is representable through the Behavioral Evidence Contract. - [ ] Verify ontology coverage of every construct used in active papers. ## P0.12 Boundary, identity, and participation - [ ] Develop and test distinctions among: - interaction attempt; - coupling event; - interaction episode; - recurrent interaction; - interaction system. - [ ] Define boundary-validity criteria rather than relying only on disclosure. - [ ] Test pause/resume, retry, multi-device continuation, nested episodes, asynchronous closure, and background participation. - [ ] Define a strict participant admission test. - [ ] Distinguish participant, mediator, resource, condition, and environment. - [ ] Evaluate one-shot and unilateral cases without forcing circular boundary expansion. ## P0.13 Construct validation and contract ablation - [ ] Validate: - opportunity profile; - believed action set; - interpretive state; - interaction strategy; - interactional equivalence; - behavioral evidence quality. - [ ] Measure inter-rater reliability. - [ ] Measure test-retest reliability. - [ ] Test convergent and discriminant validity. - [ ] Test sensitivity to manipulation. - [ ] Test calibration and inference failure conditions. - [ ] Test stability across populations, tasks, and contexts. - [ ] Ablate contract fields and measure explanatory, predictive, and intervention loss. - [ ] Compare full contracts against simpler baseline models. ## P0.14 Causal architecture - [ ] Distinguish definitional counterfactual dependence, mechanistic dependence, statistical association, and intervention-supported causation. - [ ] Specify causal graphs, confounders, mediators, moderators, interventions, estimands, and identification assumptions. - [ ] Model carryover, learning, interference, and nonstationarity. - [ ] Establish when projection effects may be attributed through opportunity, interpretation, or strategy. - [ ] Require causal claims to identify design and assumptions explicitly. ## P1.15 Continuous, embodied, concurrent, and distributed interaction - [ ] Evaluate hybrid-system, dynamical, stochastic, process, event-structure, and Petri-net formalisms. - [ ] Support continuous time and weak segmentation. - [ ] Support parallel and partially ordered activity. - [ ] Support partial observability and participant-local state. - [ ] Support embodied trajectories and sensorimotor coordination. - [ ] Support institutionally distributed authority and delayed consequences. - [ ] Avoid forcing all phenomena into discrete event logs. ## P1.16 Strategy and transfer identity - [ ] Define strategy identity independently of successful transfer. - [ ] Preregister strategy invariants before observing target outcomes. - [ ] Distinguish parameter adjustment, tactic substitution, adaptation, and strategy replacement. - [ ] Define transfer carriers without circular reliance on transfer success. - [ ] Test competing strategy and transfer models. ## P1.17 Culture and institutional mediation - [ ] Develop a positive account of convention, role, norm, authority, sanction, practice, negotiated meaning, and division of labor. - [ ] Incorporate activity theory, ethnomethodology, conversation analysis, practice theory, anthropology, and organizational studies. - [ ] Preserve non-essentialism and prohibit demographic inference without independent justification. - [ ] Treat institutions and culture as possible mechanisms, not merely confounders. ## P1.18 Adversarial benchmark independent of Fundamental - [ ] Build cases involving improvised social interaction, contested meaning, changing ontology, distributed authority, continuous coordination, ambiguous boundaries, asynchronous closure, unstable semantic state, and non-deterministic interpretation. - [ ] Compare Fundamental against CompInt rather than allowing Fundamental to define the evaluation space. - [ ] Record where Fundamental cannot represent relevant phenomena. ## P1.19 Comparative scientific gain - [ ] Compare: 1. transition-system baselines; 2. integrated HCI/cognitive-science accounts; 3. process-mining or workflow accounts; 4. full CompInt; 5. ablated CompInt variants. - [ ] Measure reliability, construct recoverability, explanatory fit, held-out prediction, intervention prediction, transfer prediction, annotation cost, reporting burden, model complexity, error detection, and practical utility. - [ ] Define success criteria before evaluation. - [ ] Treat failure to outperform integrated alternatives as a valid scientific result. ## P1.20 First decisive empirical study - [ ] Study: holding target semantics and feasible operations constant, test how projection exposure and signaling affect discovery, believed availability, action selection, error, and recovery. - [ ] Freeze all required contracts before data collection. - [ ] Define direct and latent outcomes separately. - [ ] Preregister hypotheses, exclusions, stopping rules, missing-data treatment, and analysis. - [ ] Compare baseline state-and-trace models against typed CompInt variables. - [ ] Test incremental explanatory and out-of-sample predictive gain. - [ ] Publish protocols, schemas, analysis code, data where permitted, deviations, failed analyses, and alternative models. --- # E. Long-term research and adoption ## P2.21 Benchmark program - [ ] Establish versioned benchmarks across GUI, CLI, API, conversational, multimodal, accessible, collaborative, safety-critical, institutional, robotic, embodied, and continuous interaction. - [ ] Maintain raw records, frozen contracts, governance, and leakage controls. ## P2.22 Reliability and replication - [ ] Test boundary coding, coupling identification, event attribution, opportunity coding, strategy inference, and comparison-gate reliability. - [ ] Conduct direct, conceptual, multi-site, transport, and robustness replications. - [ ] Track cross-laboratory reproducibility. ## P2.23 Prediction and intervention validation - [ ] Test discovery, invalid-attempt, error, recovery, transfer, and strategy prediction. - [ ] Test calibration, abstention, cross-projection transport, and intervention gain. - [ ] Compare against strong integrated baselines. ## P3.24 Disciplinary-threshold review - [ ] Revisit disciplinary status only after evidence of replicated mechanisms, stable validity domains, predictive or intervention gain, unique explanatory necessity, shared benchmarks, independent adoption, and a sustained research community. - [ ] Do not revisit the determination based on conceptual completeness alone. --- # F. Immediate execution order ## Release closeout 1. [x] Audit the lossless refactor against all previous packages and close any preservation gaps. *(Agent-reported.)* 2. [~] Finalize `AUTHORITY.md`, `DOCUMENT_MAP.md`, the concept registry, and the release manifest. *(Core artifacts reported complete; direct metadata inspection remains.)* 3. [~] Run terminology, definition, symbol, contract, and schema consistency checks over the active corpus. *(Terminology, definitions, schemas, and examples reported complete; symbol and contract-field consistency remain.)* 4. [ ] Apply the publication style guide to the complete repository. 5. [ ] Complete authority verification for references actually cited in the publication. 6. [~] Validate schemas, examples, derivatives, checksums, and ZIP integrity. *(Schemas, examples, checksums, tests, and ZIP integrity reported complete; source-to-derivative equivalence remains.)* 7. [ ] Obtain independent technical, methods, and ethics/community reviews. 8. [ ] Publish the Version 1.0 release and preservation archive. ## Version 2.0 launch 1. [ ] Complete the cross-paper consistency review. 2. [ ] Specify boundary, identity, and participant validation studies. 3. [ ] Design the contract-ablation and construct-validation program. 4. [ ] Specify the causal architecture. 5. [ ] Build adversarial and comparative benchmarks. 6. [ ] Preregister the first decisive empirical study. --- # Current overall status **Version 1.0 conceptual corpus:** substantially complete. **Repository consolidation:** complete; preservation and lineage audit reported complete. **Canonical integration:** glossary, ontology, identifiers, terminology, and status determination reported consistent; direct artifact-level review remains for symbols, contract metadata, and manifest completeness. **Publication infrastructure:** substantially complete, pending corpus-wide application and final proofing. **Bibliography:** normalized and audited; authoritative verification remains incomplete for the final cited set. **Empirical validation:** not complete; belongs to Version 2.0. **Independent scientific status:** not established and must not be claimed in Version 1.0. ======================================================================== ## FILE: docs/90_Project/Version_2/Validation_Matrix.csv (10 lines, 1.4 KiB) ======================================================================== priority,workstream,primary_gap,required_test,comparison_baseline,decision_output 1,Canonical consistency,Term and contract drift,Cross-paper schema and symbol audit,Version 1.0 canonical registry,Compatible or conflict report 2,Boundary and identity,Boundary declarations lack adjudication,Adversarial episode segmentation study,Independent expert boundaries,Boundary validity criteria 3,Construct validation,Analytical roles lack validation,Reliability and construct-validity studies,Simpler observable proxies,Validated or unsupported construct status 4,Contract ablation,Ontology may exceed evidence,Field-removal ablation,Reduced contract variants,Retain simplify or remove recommendation 5,Causal architecture,Causality underdeveloped,Intervention and identification studies,Associational models,Causal claim classes and estimands 6,Strategy and transfer,Circular identity inference,Preregistered invariant tests,Policy and tactic baselines,Independent strategy identity rule 7,Continuous interaction,Discrete bias,Hybrid and continuous case benchmark,Event-log discretization,Formal coverage limits 8,Fundamental independence,Platform-shaped ontology,Adversarial non-Fundamental cases,Fundamental-native representations,External validity assessment 9,Comparative gain,Distinct science not demonstrated,Multi-framework benchmark,Integrated adjacent theories,Incremental scientific gain estimate ======================================================================== ## FILE: docs/90_Project/Version_2/Version_2_Research_Program.md (57 lines, 4.3 KiB) ======================================================================== # Foundations of Computational Interaction — Version 2.0 Research Program ## Status Non-normative research agenda. Nothing in this directory modifies Version 1.0 definitions, ontology, contracts, or formal semantics. ## Scientific threshold Version 1.0 is a coherent and formalizable interdisciplinary synthesis. Version 2.0 must determine whether its distinctions produce reliable, valid, causal, predictive, or intervention-relevant gains sufficient to justify their complexity. ## Workstream 1 — Cross-paper consistency and canonical registry Maintain one stable term ID, current label, canonical definition, status, dependencies, superseded definitions, forbidden synonyms, version history, validation status, and supporting or failed studies. Before formal revision, test symbol consistency, contract compatibility, participant scope, boundary assumptions, trace segmentation, uncertainty representation, and construct coverage. ## Workstream 2 — Boundary, identity, and participation Develop principled tests for interaction attempts, coupling events, interaction episodes, recurrent interactions, and interaction systems. Specify episode initiation, suspension, resumption, nesting, splitting, termination, asynchronous closure, and multi-device continuation. Establish a participant admission test that distinguishes participants from passive resources and environmental conditions. ## Workstream 3 — Construct validation and contract ablation Validate opportunity profiles, believed action sets, interpretive states, interaction strategies, interactional equivalence, and behavioral evidence quality. Measure inter-rater and test–retest reliability, convergent and discriminant validity, sensitivity to manipulation, calibration, stability, and failure conditions. Ablate contract fields to determine whether each distinction provides measurable explanatory or predictive gain. ## Workstream 4 — Causal architecture Distinguish definitional counterfactual dependence, mechanistic dependence, statistical association, and intervention-supported causation. Specify causal graphs, confounders, mediators, moderators, interventions, identification assumptions, estimands, learning, carryover, and participant interference. ## Workstream 5 — Continuous and distributed interaction Evaluate hybrid dynamics, continuous time, concurrency, partial observability, weak segmentation, embodied trajectories, ambient systems, institutional processes, and distributed coordination without forcing all phenomena into discrete event logs. ## Workstream 6 — Strategy and transfer Define strategy identity independently of transfer outcomes. Preregister strategy invariants, admissible parameter changes, tactic substitutions, adaptation criteria, and replacement criteria before observing target-task performance. ## Workstream 7 — Culture and institutional mediation Model conventions, roles, norms, authority, sanctions, practices, negotiated meaning, institutional memory, and division of labor as mechanisms without demographic essentialism. Expand engagement with activity theory, ethnomethodology, conversation analysis, practice theory, anthropology, and organizational studies. ## Workstream 8 — Adversarial evaluation independent of Fundamental Test improvised social interaction, contested meaning, changing ontology, distributed authority, continuous coordination, ambiguous boundaries, asynchronous closure, unstable semantic state, and nondeterministic interpretation. Fundamental is an evaluation target, not an ontology source. ## Workstream 9 — Comparative scientific gain Compare transition-system, HCI/cognitive-science, process-mining, full FCI, and ablated FCI accounts. Evaluate annotation agreement, construct recovery, explanatory fit, held-out prediction, intervention prediction, transfer prediction, cost, complexity, reporting burden, error detection, and decision utility. ## Conformance profiles to evaluate - Minimum reporting core - Comparative study profile - Latent-inference profile - Causal study profile - Full foundational profile ## Decision rule A construct or contract field advances only when evidence shows that it improves reliability, validity, explanation, prediction, intervention, or scientific coordination enough to justify its operational cost. Conceptual completeness alone is insufficient. ======================================================================== ## FILE: docs/CHANGELOG.md (71 lines, 10.5 KiB) ======================================================================== # Changelog Corpus / theory layer. The C reference substrate versions **independently** — see [`../app/RELEASE_NOTES.md`](../app/RELEASE_NOTES.md) and [`../app/VERSIONING.md`](../app/VERSIONING.md). A shared number never implies cross-layer conformance. ## Unreleased - **Regenerated `llms.txt` / `llms-full.txt`** to include the runnable-demo README section (they predated it). This is the exact drift issue #27 exists to gate — the committed machine-readable corpus fell behind a docs change with nothing to catch it. Until #27 lands, regenerate with `python3 scripts/gen-llms.py` after any docs change. - **The root README now opens with something you can run.** `make demo && ./build/door` prints `state=1 events=1 hash=…` in about thirty seconds — one bounded state cell, one authorized action, one committed transition, one stable hash. It was documented only at line 60 of `app/README.md`, so a first-time reader met several hundred lines of ontology before encountering any evidence the substrate executes. The hash is the part that matters: the same declaration produces the same number on any conforming build, under GCC or Clang, which is the corpus's central claim reduced to one checkable line. - **Added `llms.txt` and `llms-full.txt`** (`scripts/gen-llms.py`), so the corpus is consumable by language models as a single artifact. The generator is built on an **allowlist**, not a filter: `LICENSES.md` states that third-party and excluded material must not be treated as project-licensed even when co-located, and that an unlisted path is *unlicensed pending classification*. Concatenating `docs/**` wholesale would have inlined third-party literature and bibliographic metadata into one file carrying the project's CC BY 4.0 banner. External literature, citation metadata, and archived releases are therefore **named in the index and never inlined** — 31 documents excluded, each with a stated reason. The full text opens with the program's own status caveat so a model ingesting it inherits the honesty framing rather than the claims alone. - **Opened the negative-results registry** ([`90_Project/Negative_Results.md`](90_Project/Negative_Results.md)), which `Research_Practices.md` §4 has mandated since it was written but which had no file. Seeded with the two hypotheses the program's **first external application** disproved: that FCI vocabulary transfers directly as an application's authoring language (the team adopted every architectural commitment and explicitly rejected the nomenclature), and that the reference substrate demonstrates operational adequacy (their requirements — jitter, dead reckoning, conflict detection under partial information — fall entirely outside the deterministic subset). Both narrow the program's claim; neither refutes it. Recorded because revising a claim erases the intuition behind it, and the abandoned intuition is what a later reader is most likely to re-propose. - **CI: replaced the third-party path-filter action with plain git.** GitHub began forcing Node 24 onto actions that target Node 20; the filter action died silently mid-run and took the whole gate with it, having passed hours earlier. A path filter is a one-line diff and does not need a dependency that can break underneath the repository. Checkout, upload-artifact and download-artifact bumped to current majors at the same time. - **Contributor guidance consolidated into tracked documentation.** The README's contributing section and `90_Project/Research_Practices.md` referenced local tooling configuration that is not part of the repository, so those pointers resolved for some contributors and broke on a fresh clone. Both now reference tracked documents only — the research practices, the authority order, the versioning policy and the verification gate. _Nothing yet._ ## 0.5.0 — 2026-07-20 **First released version.** This supersedes two earlier labels, **neither of which was ever tagged or published**: - `1.0.0` claimed a ratification that has not occurred — ontology labels remain pending identifier ratification, and the program's own stance is that its scientific necessity and empirical advantage remain to be demonstrated. - `0.9.0` still implied *approaching release*, which overstates how settled the theory is. `0.5.0` is the honest position: substantial work exists, and it is nowhere near a stable commitment. Everything previously recorded under those labels ships here — the entries are retained below rather than discarded. - **README accuracy corrections.** The `90_Project/` row omitted `Reviews/` and `Research_Practices.md`. The CI table understated `ci.yml`, which runs a **gcc + clang matrix** and compares the `make conformance` vectors across compilers — the comparison, not the two passing builds, is what tests the determinism claim. - **Theory version corrected downward, 1.0.0 → 0.5.0** (via a briefly-held `0.9.0`, never tagged). The 1.0 label claimed a ratification that has not occurred: ontology labels are still pending identifier ratification, and the program's own stance is that its scientific necessity and empirical advantage remain to be demonstrated. **No theory content changed** — this is a relabelling, not a revision. Records that cite "theory 1.0.0" (example alignment records, prior release notes, editorial reports) are deliberately left unedited, because rewriting them would misstate what was validated when. Nothing was ever tagged or released at 1.0.0, so no published artifact contradicts the change. - The two top-level v1.0 records — the comprehensive repository review and the program closeout TODO — were **moved, not deleted**, to `90_Project/Reviews/`. They are 783 lines of unique material with no equivalent anywhere else in the corpus; the canonical-cleanup intent was to clear the top level, which a move achieves without destroying the record. - **Working practices documented and made checkable.** Operational conventions — layout, authority order, the verification gate, CI, per-layer versioning and changelogs, branch and commit conventions — are now written down alongside the research-claim practices they depend on. - Added [`90_Project/Research_Practices.md`](90_Project/Research_Practices.md): maturity vs provenance as independent dimensions, preregistration, the discovery criterion (a discovery must show the prior basis *could not in principle* have exposed it), permanence of negative results, the structural/representational/convenience classification, and an explicit section on what these practices do **not** establish. - **Corrected `docs/README.md`, which was stale in both directions**: it described `00_Project/`, `03_Research_Infrastructure/` and `04_External_Literature/`, none of which exist, and omitted `03_External_Literature/`, `04_Reference/`, `05_Publication/` and `90_Project/`, which do. Every link check had passed throughout — the link checker validates links, not claims about structure. - Added `scripts/check-structure.py`, now gated in CI, which verifies documented directory claims against the filesystem in both directions (described-but-absent and present-but-undescribed). It found the seven drifts above. - **Repository renamed** to `foundations-of-computational-interaction` (from `CompInt`), matching the program's full name. GitHub redirects the old URL; local clones should update their remote. - **Continuous integration added** (`.github/workflows/`), modelled on the Fundamental engine's gate discipline and adapted to FCI's per-layer versioning: - `ci.yml` builds and tests the C reference substrate under **both gcc and clang**, then asserts the `make conformance` vectors are **byte-identical across compilers** — determinism across toolchains is the substrate's actual claim, and each build passing its own tests would not test it. A mandatory `conclusion` job asserts every dependency succeeded, so a skipped or cancelled job can never count as green. - `pr-checks.yml` enforces record-keeping **per layer** rather than repo-wide: a PR touching `docs/` must add to `docs/CHANGELOG.md`, a PR touching `app/` must add to `app/RELEASE_NOTES.md`. A single shared changelog would imply exactly the cross-layer coupling `app/VERSIONING.md` exists to deny. A further check flags multi-layer version bumps whose description does not address coupling. - **Corpus link integrity is now gated** (`scripts/check-doc-links.py`): every internal markdown link must resolve. First run found one broken link across the 94 markdown files in the corpus — a `_archive/` reference in the README to a directory that does not exist. - **README rewritten** for accuracy: removed the non-existent `_archive/` layer, documented the real directory inventory, stated what the C substrate does *and does not* establish, surfaced the per-layer versioning table, and documented the verification gate. - Added the **Scientific Project Audit and Grading Standard** (`04_Reference/Handbooks/Scientific_Project_Audit_Standard/`, v0.1.0-draft): fatal validity gates, twelve scientific dimensions, formula/scoring rules, project-type profiles, reporting standard, worked examples, governance, and reusable audit report/scorecard templates. - Standardized program naming to **Foundations of Computational Interaction (FCI)**, replacing the interim "the proposed model" placeholder and residual "CIS" usages; the acronym is defined on first use per document. Example identifiers (`CIS-EX-*`) are unchanged. - Added machine-checkable governance schemas: `ethics-gate-assessment.schema.json` (the eight non-compensatory ethics/power gates) and `data-management-plan.schema.json`. - Corpus hygiene: repaired an OCR-garbled bibliography block in the Canonical Glossary, corrected a stray bibliography count (600 → 267 canonical), and repaired a corrupted terminology change-log and package reference in the consolidation records. - `scripts/check-doc-links.py` now enumerates **tracked** markdown via `git ls-files` rather than walking the filesystem. It was scanning untracked local files, so a local run could fail where CI — which never sees them — passed. Repository link integrity is a property of tracked content. ### Previously recorded under the unreleased `1.0.0` label Initial clean corpus release. - Organized research papers by dependency order. - Established the knowledge system of record. - Separated generated research artifacts from external literature. - Consolidated existing contracts into a derivative specification. - Removed operating-system metadata, obsolete duplicates, and temporary audit or migration reports. - Normalized filenames to `Title_Case_With_Underscores.ext`. - Preserved all active theoretical, reference, and source content. ======================================================================== ## FILE: docs/README.md (20 lines, 1.2 KiB) ======================================================================== # Foundations of Computational Interaction Version **0.5.0** This repository contains the Foundations of Computational Interaction research corpus, its knowledge system of record, supporting research infrastructure, and external literature. ## Structure - `01_Knowledge_System_of_Record/` — ontology, glossary, encyclopedia, framework, contracts, graphs, and reviews. - `02_Research_Papers/` — research papers in dependency order. - `03_External_Literature/` — external books, papers, and reports only. - `04_Reference/` — bibliography, citation maps, reading guides, dataset schemas, templates, and the audit standard. - `05_Publication/` — publication guidelines and consistency audits. - `90_Project/` — repository metadata, release history, audits, decisions, manifests, and research practices. ## File naming Files use `Title_Case_With_Underscores.ext`. Standard repository files retain conventional uppercase names such as `README.md`, `VERSION`, and `CHANGELOG.md`. The knowledge system of record is authoritative for consolidated terminology. Source research papers remain authoritative for their original arguments and evidence until normative consolidation is ratified. ======================================================================== ## FILE: docs/ROADMAP.md (5 lines, 0.3 KiB) ======================================================================== # Roadmap Version 1.0 is the frozen conceptual synthesis and publication corpus. Version 2 work is isolated under `90_Project/Version_2` and concerns empirical validation, boundary and identity theory, causal architecture, continuous and distributed interaction, construct validation, contract ablation, and comparative scientific gain. ======================================================================== ## FILE: docs/START_HERE.md (18 lines, 1.3 KiB) ======================================================================== # Start Here This repository has one working structure and one archive. 1. `01_Knowledge_System_of_Record` — canonical concepts, definitions, specifications, registry, indexes, and graphs. 2. `02_Research_Papers` — scholarly arguments and provenance. 3. `03_External_Literature` — supporting literature retained with the corpus. 4. `04_Reference` — bibliography, citation maps, handbooks, templates, schemas, and figures. 5. `05_Publication` — style guidance, editorial reports, publication reports, and bibliography audits. 6. `90_Project` — decisions, audits, Version 2 planning, manifests, and unchanged historical releases. ## Authority The Knowledge System of Record is authoritative for definitions and contracts. Research papers provide argument and provenance. The canonical registry is an index inside the Knowledge System of Record, not a second source of truth. The verified bibliography under `04_Reference/Bibliography/Verified_v1.1.2` supersedes earlier bibliography exports for publication use. ## Lossless refactor No source release package was deleted. Every input package is preserved byte-for-byte under `90_Project/Previous_Releases`. Active files were reorganized into a simpler working tree. Consult `90_Project/Manifests/FILE_MANIFEST.csv` and `MIGRATION_MAP.md` for traceability. ======================================================================== ## FILE: docs/VERSION (1 lines, 0.0 KiB) ======================================================================== 1.0.0 ======================================================================== ## FILE: scripts/check-doc-links.py (92 lines, 3.4 KiB) ======================================================================== #!/usr/bin/env python3 """Verify that every internal markdown link in the corpus resolves. A research corpus is a citation graph. A dead internal link is a broken citation, and in a repository whose whole claim is traceability that is a correctness bug, not a formatting nit. Checks relative links and anchors-with-paths; deliberately ignores external URLs (network-blocked CI must not depend on the reachability of third-party sites) and pure in-page anchors. python3 scripts/check-doc-links.py [--quiet] """ from __future__ import annotations import re import subprocess import sys import urllib.parse from pathlib import Path ROOT = Path(__file__).resolve().parent.parent SKIP_DIRS = {".git", "node_modules", "build", "_archive", ".agents"} # [text](target) — not preceded by `!` (images are checked too, but via the same rule) LINK = re.compile(r"(? list[Path]: """Tracked markdown only. Walking the filesystem would also scan untracked local files (editor config, scratch notes), which CI never sees — so a local run could fail where CI passed. Repository link integrity is a property of tracked content. Falls back to a filesystem walk outside a git checkout. """ try: out = subprocess.run( ["git", "-C", str(ROOT), "ls-files", "-z", "*.md"], capture_output=True, check=True, text=True, ).stdout tracked = [ROOT / n for n in out.split("\0") if n] if tracked: return [p for p in tracked if p.exists() and not any(part in SKIP_DIRS for part in p.relative_to(ROOT).parts)] except (subprocess.CalledProcessError, FileNotFoundError): pass return [p for p in ROOT.rglob("*.md") if not any(part in SKIP_DIRS for part in p.relative_to(ROOT).parts)] def is_external(target: str) -> bool: return target.startswith(("http://", "https://", "mailto:", "tel:", "ftp://", "//")) def main() -> int: quiet = "--quiet" in sys.argv files = markdown_files() broken: list[tuple[Path, str, int]] = [] checked = 0 for path in files: try: text = path.read_text(encoding="utf-8") except UnicodeDecodeError: continue for lineno, line in enumerate(text.splitlines(), 1): for raw in LINK.findall(line): target = raw.strip() if not target or is_external(target) or target.startswith("#"): continue # strip the fragment; a path must resolve even if its anchor is not verified path_part = urllib.parse.unquote(target.split("#", 1)[0]) if not path_part: continue checked += 1 resolved = (path.parent / path_part).resolve() if not resolved.exists(): broken.append((path.relative_to(ROOT), target, lineno)) if broken: print(f"✗ {len(broken)} broken internal link(s):\n") for rel, target, lineno in sorted(broken)[:60]: print(f" {rel}:{lineno} → {target}") if len(broken) > 60: print(f" … and {len(broken) - 60} more") return 1 if not quiet: print(f"✓ internal doc links ok — {checked} link(s) across {len(files)} markdown files") return 0 if __name__ == "__main__": raise SystemExit(main()) ======================================================================== ## FILE: scripts/check-structure.py (66 lines, 2.2 KiB) ======================================================================== #!/usr/bin/env python3 """Verify that directories described in prose actually exist. The link checker validates links; it does not validate *claims about structure*. `docs/README.md` described two directories that did not exist and omitted three that did, and every link check passed the whole time. This closes that specific gap. Scans the documentation files listed in TARGETS for backticked directory references of the form `NN_Name/` and checks each against the filesystem, in both directions: - described but absent → the document is stale - present but undescribed → the document is incomplete python3 scripts/check-structure.py [--quiet] """ from __future__ import annotations import re import sys from pathlib import Path ROOT = Path(__file__).resolve().parent.parent # (document, directory it describes) TARGETS = [ (ROOT / "docs" / "README.md", ROOT / "docs"), (ROOT / "README.md", ROOT / "docs"), ] # `01_Knowledge_System_of_Record/` — numbered corpus directories only, so ordinary prose that # happens to contain a slash is not mistaken for a structural claim. REF = re.compile(r"`(\d{2}_[A-Za-z0-9_]+)/`") def main() -> int: quiet = "--quiet" in sys.argv problems: list[str] = [] checked = 0 for doc, directory in TARGETS: if not doc.exists() or not directory.exists(): continue described = {m for m in REF.findall(doc.read_text(encoding="utf-8"))} if not described: continue actual = {p.name for p in directory.iterdir() if p.is_dir() and re.match(r"\d{2}_", p.name)} rel = doc.relative_to(ROOT) checked += len(described) for name in sorted(described - actual): problems.append(f" {rel}: describes `{name}/` — no such directory in {directory.relative_to(ROOT)}/") for name in sorted(actual - described): problems.append(f" {rel}: does not describe `{name}/`, which exists") if problems: print(f"✗ {len(problems)} structure claim(s) do not match the filesystem:\n") print("\n".join(problems)) return 1 if not quiet: print(f"✓ structure claims ok — {checked} directory reference(s) verified") return 0 if __name__ == "__main__": raise SystemExit(main()) ======================================================================== ## FILE: scripts/gen-llms.py (189 lines, 7.8 KiB) ======================================================================== #!/usr/bin/env python3 """Generate llms.txt and llms-full.txt for the FCI corpus. `llms.txt` is an index (llmstxt.org): what this program is, what it does not claim, and where each document lives. `llms-full.txt` concatenates the **project-licensed corpus** into one file. Generates versioned llms index and full codebase corpus files in `.agents/` and top-level root: .agents/llms.txt .agents/llms-fci-v.txt .agents/llms-full.txt .agents/llms-full-fci-v.txt """ from __future__ import annotations import os import re import subprocess import sys from pathlib import Path ROOT = Path(__file__).resolve().parent.parent AGENTS_DIR = ROOT / ".agents" SITE = "https://github.com/zachshallbetter/foundations-of-computational-interaction/blob/main" # Project-licensed prose (CC BY 4.0) — safe to inline. INCLUDE_DIRS = [ ("docs/01_Knowledge_System_of_Record", "Canonical definitions, glossary, relational ontology, contract definitions"), ("docs/02_Research_Papers", "Research papers in logical dependency order"), ("docs/05_Publication", "Publication guidelines and consistency audits"), ("docs/90_Project", "Release manifests, audits, decisions, research practices, negative results"), ] INCLUDE_APP_DOCS = True ROOT_DOCS = [ "README.md", "LICENSES.md", "AGENTS.md", "CLAUDE.md", "docs/README.md", "docs/START_HERE.md", "docs/CHANGELOG.md", "docs/ROADMAP.md", ".agents/AGENTS.md" ] EXCLUDE = { "docs/03_External_Literature": "third-party literature — excluded from project licensing, retained under original terms", "docs/04_Reference": "bibliographic records and citation metadata — mixed/third-party, not project-licensed", "docs/90_Project/Previous_Releases": "bundled historical releases — inherit-original, archived byte-for-byte", "_archive": "bundled historical releases — inherit-original", } def get_version() -> str: try: out = subprocess.run(["git", "-C", str(ROOT), "describe", "--tags", "--abbrev=0"], capture_output=True, check=True, text=True).stdout.strip() if out: return out.lstrip("v") except Exception: pass return "0.5.0" def is_excluded(rel: str) -> str | None: for path, reason in EXCLUDE.items(): if rel == path or rel.startswith(path + "/"): return reason return None def tracked_markdown() -> list[Path]: """Tracked files only — untracked local notes are not corpus.""" try: out = subprocess.run(["git", "-C", str(ROOT), "ls-files", "-z", "*.md"], capture_output=True, check=True, text=True).stdout return [ROOT / n for n in out.split("\0") if n] except (subprocess.CalledProcessError, FileNotFoundError): return sorted(ROOT.rglob("*.md")) def h1_of(path: Path) -> str: for line in path.read_text(encoding="utf-8", errors="replace").splitlines(): if line.startswith("# "): return line[2:].strip() return path.stem.replace("_", " ") def main() -> int: version = get_version() agents_dir = AGENTS_DIR agents_dir.mkdir(parents=True, exist_ok=True) all_md = tracked_markdown() included: list[Path] = [] skipped: list[tuple[str, str]] = [] allowed_prefixes = [d for d, _ in INCLUDE_DIRS] + (["app"] if INCLUDE_APP_DOCS else []) + [".agents"] for p in all_md: rel = p.relative_to(ROOT).as_posix() reason = is_excluded(rel) if reason: skipped.append((rel, reason)) continue if rel in ROOT_DOCS or any(rel.startswith(pre + "/") for pre in allowed_prefixes): included.append(p) else: skipped.append((rel, "not on the project-licensed allowlist (LICENSES.md: unlisted ⇒ unlicensed pending classification)")) included.sort(key=lambda p: p.relative_to(ROOT).as_posix()) # ---- llms.txt (index) idx = [ "# Foundations of Computational Interaction (FCI)", f"> Version: v{version} | Total Included Documents: {len(included)}", "", "> An interdisciplinary research program for formally describing, measuring, modeling, and", "> predicting human–computer interaction. It is a **research program, not an established", "> discipline** — its scientific necessity and empirical advantage remain to be demonstrated.", "> Nothing here is a validated result unless a record says so explicitly.", "", "Versions move **independently per layer**; a shared number never implies cross-layer conformance.", f"Theory {version} (pre-ratification) · contract schemas 0.2.0 · dataset schema 0.3.0 ·", "C reference substrate 0.1.0. Passing the substrate's tests establishes reference-kernel", "conformance only — not empirical validation.", "", f"- [llms-full.txt]({SITE}/llms-full.txt): the project-licensed corpus concatenated into one file", f"- [llms-full-fci-v{version}.txt]({SITE}/llms-full-fci-v{version}.txt): versioned corpus payload", "", ] for d, desc in INCLUDE_DIRS: docs = [p for p in included if p.relative_to(ROOT).as_posix().startswith(d + "/")] if not docs: continue idx += [f"## {Path(d).name.replace('_', ' ')}", "", f"{desc}.", ""] for p in docs: rel = p.relative_to(ROOT).as_posix() idx.append(f"- [{h1_of(p)}]({SITE}/{rel})") idx.append("") idx += ["## Excluded from the full text", "", "Named here rather than inlined, because `LICENSES.md` forbids treating them as", "project-licensed even when co-located:", ""] for path, reason in EXCLUDE.items(): idx.append(f"- `{path}` — {reason}") idx.append("") idx_text = "\n".join(idx) # ---- llms-full.txt full = [ "# Foundations of Computational Interaction — full corpus", f"Version: v{version} | Total Included Documents: {len(included)}", "", "Generated from the project-licensed corpus only. Third-party literature, bibliographic", "metadata and archived releases are deliberately absent — see LICENSES.md.", "", "Prose is CC BY 4.0; `app/**` documentation describes Apache-2.0 code.", "", "FCI is a research program, not an established discipline. Its scientific necessity and", "empirical advantage remain to be demonstrated.", "", "=" * 78, "", ] for p in included: rel = p.relative_to(ROOT).as_posix() full += [f"", "", p.read_text(encoding="utf-8", errors="replace").rstrip(), "", "=" * 78, ""] full_text = "\n".join(full) # Write to .agents/ (agents_dir / "llms.txt").write_text(idx_text, encoding="utf-8") (agents_dir / f"llms-fci-v{version}.txt").write_text(idx_text, encoding="utf-8") (agents_dir / "llms-full.txt").write_text(full_text, encoding="utf-8") (agents_dir / f"llms-full-fci-v{version}.txt").write_text(full_text, encoding="utf-8") # Write to root (for backwards compatibility) (ROOT / "llms.txt").write_text(idx_text, encoding="utf-8") (ROOT / f"llms-fci-v{version}.txt").write_text(idx_text, encoding="utf-8") (ROOT / "llms-full.txt").write_text(full_text, encoding="utf-8") (ROOT / f"llms-full-fci-v{version}.txt").write_text(full_text, encoding="utf-8") kib = (agents_dir / "llms-full.txt").stat().st_size // 1024 print(f"✓ gen-llms: generated .agents/llms.txt, .agents/llms-fci-v{version}.txt and .agents/llms-full.txt, .agents/llms-full-fci-v{version}.txt ({kib} KiB) — {len(included)} documents included") by_reason: dict[str, int] = {} for _, reason in skipped: by_reason[reason] = by_reason.get(reason, 0) + 1 for reason, n in sorted(by_reason.items(), key=lambda kv: -kv[1]): print(f" excluded {n:>3} {reason}") return 0 if __name__ == "__main__": raise SystemExit(main())