EVEMISSLAB

ResearchRES-2026-0001v0.1

Blind derivation of an adaptive epistemic architecture

Starting only from first principles — temporally heterogeneous world knowledge, canonical symbolic state, adaptive representation space, capability memory, substrate-neutral compute — the eleven-paper series derives a candidate architecture and then asks the uncomfortable question the derivation raised: why does it look so much like modern compound AI, and does any of the difference survive into a runtime?

Research status
ACTIVE under continuous research
Evidence level
E2 Controlled experiment
Data basis
THEORY Theoretical reasoning only; no measurement.
Version
0.1
Updated
2026-09-08
Created
2026-09-07
Domain
AI Architecture, Context & Memory, Agent Systems, AI-native Systems
Program
PRG-2026-0001 Adaptive Epistemic Systems
Authors
Neo.K (EveMissLab)
AI collaborators
Sol (GPT-5.6, OpenAI ChatGPT)

Research questions

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)?

Claims

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).

Limitations

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).

Relations

SourceRelationTargetStatusID
RES-2026-0001 Blind derivation of an adaptive epistemic architecturebelongs_toPRG-2026-0001 Adaptive Epistemic SystemsACTIVEREL-2026-0001
RES-2026-0001 Blind derivation of an adaptive epistemic architecturedevelopsTHY-2026-0001 Asymmetric spacetime tension: temporally heterogeneous world knowledgeACTIVEREL-2026-0007
RES-2026-0001 Blind derivation of an adaptive epistemic architecturedevelopsTHY-2026-0002 Canonical symbolic state and candidate → verify → commit authorityACTIVEREL-2026-0008
RES-2026-0001 Blind derivation of an adaptive epistemic architecturedevelopsTHY-2026-0003 Intelligent architecture attractorACTIVEREL-2026-0010
RES-2026-0001 Blind derivation of an adaptive epistemic architecturedevelopsTHY-2026-0004 Probability is not Bayesian; Bayes cannot self-authorize its premisesACTIVEREL-2026-0013
RES-2026-0001 Blind derivation of an adaptive epistemic architecturedevelopsTHY-2026-0007 Capability memory and substrate-neutral compute: Reuse ≻ Adapt ≻ CreateACTIVEREL-2026-0017
RES-2026-0003 Does epistemic governance survive implementation? The AER-0 architecture comparisonextendsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0005
PAP-2026-0001 Paper 01 — Dynamic knowledge graphs under asymmetric spacetime tensionreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0018
PAP-2026-0002 Paper 02 — Stability is not a static value: freshness, decay and update tensionreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0021
PAP-2026-0003 Paper 03 — From dynamic graph to executable symbolic system: language as rendering, not canonical statereportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0024
PAP-2026-0004 Paper 04 — World-knowledge expansion and the adaptive representation spacereportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0027
PAP-2026-0005 Paper 05 — Memory, algorithm libraries and reusable solution pathsreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0029
PAP-2026-0006 Paper 06 — Substrate-neutral computational containersreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0032
PAP-2026-0007 Paper 07 — Blind-derived AI: do different first principles converge on one engineering form?reportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0035
PAP-2026-0008 Paper 08 — Intelligent architecture attractors: at which level does difference live?reportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0038
PAP-2026-0009 Paper 09 — Probability is not BayesianreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0041
PAP-2026-0010 Paper 10 — Bayes within Bayes: who authorizes the update rule?reportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0044
PAP-2026-0011 Paper 11 — If it is really stronger, I was wrong; if not, what did we find? The final experimental verdictreportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0047
PAP-2026-0013 Adaptive Epistemic AI Runtime — technical whitepaper v0.1reportsRES-2026-0001 Blind derivation of an adaptive epistemic architectureACTIVEREL-2026-0053

History and provenance

Canonical URL
https://evemisslab.com/ai/research/RES-2026-0001/
Machine-readable
/ai/research/RES-2026-0001/index.json
Snapshot
AI-SNAPSHOT-v0.1-fe85b9694a45
Provenance
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