Independent Researcher Structure Recognition Program Hub

Jonghun Choi / 최종훈

Independent Researcher · 2nd-Year Student at Inha Technical College

Core Epistemological Question
“How do humans come to see something new?”

About the Research

I am an independent researcher and a second-year student at Inha Technical College, conducting a long-term research program on Structure Recognition — the study of how humans discover structure, assign meaning to it, and generate new research questions from what they observe.

My research began with a simple empirical observation: certain patterns in 4-variable Karnaugh maps — like the checkerboard formed by XOR/XNOR functions — feel visually distinct from other Boolean function patterns. That intuition evolved into a series of interconnected investigations into structural invariance, topological equivalence under variable permutations, and the cognitive mechanisms underlying mathematical insight.

A Starting Insight & Active Direction
The 4-variable Boolean function space contains exactly 216 = 65,536 distinct functions. Under axis-swap symmetry — where F(A,B,C,D) = F(C,D,A,B) — these functions are not all structurally independent. Some are symmetric under the swap, some form pairs, and others form larger orbits.

Research Question: When the 65,536 functions are classified by axis-swap symmetry and gate generators, how many distinct equivalence classes result? This question bridges group theory and combinatorics. It was first explored in the archived Paper 6 (Boolean Function Space Theory) and is now treated in the current Paper 7, a standalone paper on the group-theoretic classification of 4-variable Boolean function spaces on Karnaugh maps.

Research Philosophy: Humans discover structure through visual and spatial intuition; AI expands the explanation space. The collaboration between human structural insight and AI's capacity for systematic combinatorial exploration is itself an object of rigorous study — not merely a convenience.

The Unified Research Program

Layers of archived early research notes (Papers 1–6) connect empirical observation to cognitive formalization and mathematical extension; the current work is the two standalone Papers 7 and 8.

Layer 1 · Empirical Foundation
Empirical Case Studies
Concrete observational data from Boolean symmetries and visual Karnaugh mappings.
Paper 1: Karnaugh Map Structure Invariance
Paper 2: Symmetric Boolean Visual Patterns
Paper 3: Variable Rearrangement Invariance
Layer 2 · Theoretical Integration
Structure Recognition Theory (SRT)
General cognitive architecture modeling how structure triggers inquiry (Hypotheses H1–H10).
Paper 4: Structure Recognition Theory (SRT Hub)
Layer 3 · Methodological Meta-Layer
Human-AI Collaboration (HARCT)
Distributed research memory across long-term autonomous sessions.
Paper 5: Human-AI Collaboration (HARCT)
Layer 4 · Mathematical Extension
Boolean Function Space Theory
Algebraic characterization and gate-generated sub-spaces.
Paper 6: Boolean Function Space Theory (archived; superseded by Paper 7)
Exploratory · Application Domains
Broader Educational & Mathematical Impact
AI Collaboration Education · Structure-Based Elementary Mathematics (research threads without a paper yet).
Synthesis · Standalone Papers
Program Synthesis (Current Papers 7 and 8)
Two standalone papers, each readable without the earlier papers of the program.
Paper 7: Group-Theoretic Classification of Boolean Function Spaces
Paper 8: Structural Thinking and Human-AI Collaboration

Central Hub Documents

Root documentation, operational protocols, and formal definitions consolidating the research program.

2026-06-21 구조 통합 (Session 33)
이전의 program/, theory/, ai-workspace/ 하위 폴더 문서들이 아래 루트 파일들로 체계적으로 통합되었습니다.
AI Single Entry Point

SESSION_START.md

  • AI 단일 진입점 (v5.4) — 프로그램 전체 구조 & AI 운영 원칙
  • Active Queue & Repository Health (작업 현황 종합)
  • Critical Workflow Rules & Program Architecture (B; Papers 1–6 archived, Papers 7–8 current)
  • Session completion records (Sessions 45–49, 2026-06) and the 2026-10 update note
Open Document ↗
Theoretical Synthesis

StructureRecognitionTheory_Unified.md

  • Formal Definitions 3.1–3.3 (Structure · Attention · Explanatory Significance)
  • H1–H10 Hypotheses — Research Generation + Concept Evolution
  • Q1–Q15 Question Hierarchy (Level 0–8), OP-01–OP-09
Full Theory Hub ↗
Proposal Outline

HumanAICollaborationProposal_Outline.md

  • Human-AI 협업 연구 제안서 개요
  • 협업 모델 · 연구 질문 생성 구조 · 장기 프로그램 설계
Open Proposal ↗

Peer Repositories

Empirical · Paper 1

KMap Structure Invariance

Structural invariance of Karnaugh map checkerboard patterns under geometric transformations.

Empirical · Paper 2

Symmetric Boolean Functions

Hamming-weight layers and concentric ring structures in symmetric Boolean function patterns.

Empirical · Paper 3

Rearrangement Invariance

Equivalence classes and symmetry preservation across input variable permutations.

Theory · Paper 4

Structure Recognition Theory

Meta-theoretical framework synthesizing Hypotheses H1–H10 on structure discovery and concept evolution.

Methodology · Paper 5

Human-AI Collaboration

HARCT framework, distributed research memory, AI handover, and multi-session continuity.

Mathematics · Paper 6

Boolean Function Space Theory

Orbit classification of the affine, monotone and self-dual subspaces of the 4-variable Boolean functions, and gate universality.

Mathematics · Paper 7 (Standalone)

Group-Theoretic Classification of Boolean Function Spaces

Classification of 4-variable Boolean function spaces on Karnaugh maps, readable without the earlier papers: variable-arrangement classes, S₄ orbits, and the signed permutation group B₄ (order 384).

Cognitive & AI · Paper 8 (Standalone)

Structural Thinking and Human-AI Collaboration

Framework proposal (SRT, HARCT), readable without the earlier papers, on human structural cognition and human-AI research, with a single-case study and educational implications.

Concept Genealogy

The sequence below records the actual developmental path of the research program — tracing discovery from intuition to formalization.

1. Pattern (Karnaugh Map Checkerboard)
First empirical observation: Alternating visual checkerboard patterns for XOR/XNOR logic functions.
2. Layer Structure (Hamming Weights)
Discovery: Hamming-weight layers mathematically govern the locations of symmetric function patterns.
3. Equivalence & Structural Invariance
Observation: Variable rearrangements preserve invariant structural topologies across map re-orderings.
4. Structure Recognition Theory (SRT)
Meta-question: Why do certain structures trigger research inquiry while others remain unnoticed?
5. Human-AI Collaboration Model (HARCT)
Division of cognitive labor: Humans discover structure intuitively; AI systematically expands the explanation space.
6. Boolean Function Space Theory (Paper 6, archived)
Former mathematical frontier (archived early notes, superseded by Paper 7): Gate-generated sub-spaces and Post's lattice as rigorous foundations.
7. Standalone Papers 7 and 8 (current)
Current work: Paper 7 (group-theoretic classification of 4-variable Boolean function spaces on Karnaugh maps) and Paper 8 (structural thinking and human-AI research collaboration), each readable without the earlier papers.

Keywords

Karnaugh map Boolean function structural invariance structure recognition symmetric Boolean function variable rearrangement Hamming weight visual pattern analysis human-AI collaboration research question generation Boolean function space Post's lattice gate universality HARCT research continuity epistemology AI in education