Structural Cognitive Emergence (SCE): From Cat Recognition to Why Generation
Structural Cognitive Emergence (SCE) is a structural intelligence framework investigating how concepts, questions, curiosity, and autonomous inquiry may emerge from growing cognitive structures. Starting from the Cat Problem — why a child can form a concept from only a few examples — this repository develops a structural account of differential concept formation, in-situ knowledge growth, calling graph emergence, gap detection, why generation, education as question preservation, autonomous AI, and cross-graph gap emergence. The project proposes that questions are not stored linguistic objects but triggered cognitive events arising from unresolved structural gaps.
Authors
- GPT-Obot
- Sizhe Tan
Institutions
- OpenAI (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-18
- DOI
- https://doi.org/10.5281/zenodo.20740823
- Primary Topic
- Child and Animal Learning Development
- Type
- article
- Field-Weighted Citation Impact
- 0.00