Structure Recognition Theory (SRT)
A formal cognitive framework for how humans detect explanatory significance and generate research questions.
Abstract
Structure Recognition Theory (SRT) investigates the cognitive mechanisms by which humans discover structures, assign meaning to them, and generate research questions. The theory proposes that research does not begin from structure detection alone, but from detecting explanatory significance — an intuitive and cognitive sense that an observed pattern warrants deeper systematic investigation.
Built on three empirical case studies (Papers 1–3 on Karnaugh map patterns, symmetric Boolean functions, and variable rearrangement invariance), SRT synthesizes ten exploratory hypotheses (H1–H10), formal definitions of Structure, Attention, and Explanatory Significance, and a hierarchy of fifteen research questions (Q1–Q15 across nine levels (Levels 0–8)).
Theoretical Hypotheses (H1–H10)
All hypotheses in SRT are exploratory models designed to generate empirical testing protocols.
| # | Hypothesis Name | Core Proposition |
|---|---|---|
| H1 | Structure Discoverer | Humans have a distinctive comparative advantage in initial structure discovery over AI systems. |
| H2 | Representation Transformation | Changing visual/geometric representations is what enables latent structure discovery. |
| H3 | Attention Filter | Not all perceptual patterns trigger exploratory investigative attention. |
| H4 | Significance Filter | Cognition applies an implicit heuristic filter: "is this structure worth investigating?" |
| H5 | Explanation Anticipation | Humans perceive that a pattern "ought to have an explanation" prior to formulating the proof. |
| H6 | Explanatory Significance | Research generation initiates from detecting explanatory potential, not raw structure alone. |
| H7 | Mature Structure Discoverer | The fundamental human research role is detecting explanation opportunities for systematic expansion. |
| H8 | Concept-as-Lens | Concepts act as observation lenses — radically altering what structures become visible. |
| H9 | Concept Evolution | Research produces concepts; refined concepts in turn generate higher-order research inquiries. |
| H10 | Generative Concept | Concepts differ in their generative capacity — fertile concepts open extensive research programs. |
Current Theory Documentation
| Document | Version | Key Contents | Repository |
|---|---|---|---|
| StructureRecognitionTheory_Unified.md | v0.3 | Formal Definitions 3.1–3.3, H4 Operationalization, Empirical Protocol §10 | inha20/ |
| Hypotheses.md | H1–H10 | Complete hypotheses with mathematical cross-references | This Repo |
| CoreQuestions.md | v2.0 | Hierarchical question taxonomy Q1–Q15 (Levels 0–8) | This Repo |
| OpenProblems.md | v1.1 | Nine active open research challenges (OP-01–OP-09) | This Repo |