智能架構吸引子

前提

assumptions

• The executed architecture is the architecture (runtime-truth principle); spec cannot defend runtime.

主張

claims

• Theory difference matters only insofar as it survives into measurable state, computation, behaviour or resource use; if it does not survive, the convergence itself becomes the phenomenon to explain.
• If every possible outcome is interpreted as confirmation, the theory has explained nothing.

預測

predictions

• Independent architectures' ablation cores intersect (an attractor core) if the attractor is real.

證偽／失敗條件

falsification_conditions

• Distinct Advantage: stable multidimensional advantage over baselines across models, seeds, tasks and horizons weakens the convergence suspicion.
• Architecture Worse: added structure is operationally unnecessary or harmful.

已知限制

known_limitations

• One implementation provides at most candidate evidence for convergence; an attractor study needs n ≫ 2 independent starting points (Paper 11 §53).

證據

關係

歷史與來源歷程

Canonical URL

https://evemisslab.com/ai/theory/THY-2026-0003/

機器可讀

/ai/theory/THY-2026-0003/index.json

快照

AI-SNAPSHOT-v0.1-fe85b9694a45

來源歷程

source

EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)

extracted_by

Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports

extracted_at

2026-09-11

generator

tools/extract_aes/extract.py

claim_boundary

status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports