自適應認識系統的盲推導

研究問題

research_questions

• What does an intelligent system look like when derived from world-state, freshness, memory and reuse requirements rather than from existing AI paradigms?
• Which of its architectural semantics — canonical state ownership, candidate→verify→commit, mandatory provenance, tension-scheduled refresh — survive comparison with progressively stronger baselines?
• If the differences do not survive, is the convergence itself the phenomenon to explain (an intelligent architecture attractor)?

主張

claims

• World knowledge is temporally heterogeneous; a single global refresh clock is either wasteful or stale.
• Natural language should be an interface to canonical state, not the canonical state.
• After removing what strong baselines already do, the candidate AER core is: epistemic world-state semantics + candidate/verify/commit authority + mandatory fact provenance + node-local tension refresh + capability/container separation + explicit epistemic-operator routing (R2).

限制

limitations

• No performance, cost or long-horizon comparison against a production agent framework has been run; R2's LangGraph comparison is source-grounded only.
• One implementation and one substrate cannot speak for all implementations, benchmarks, model families or substrates (Paper 11 §114).

關係

歷史與來源歷程

Canonical URL

https://evemisslab.com/ai/research/RES-2026-0001/

機器可讀

/ai/research/RES-2026-0001/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