ProgramPRG-2026-0001v0.1
Adaptive Epistemic Systems
A research program that derives an AI runtime from first principles — world knowledge changes at heterogeneous rates, natural language is a rendering rather than the canonical state, capability must be remembered and reused, algorithm and compute substrate are separate — and then forces the derivation into executable reality: the AER-0 reference runtime with six architecture-comparison rounds, and the PACC micro-lab on whether non-probabilistic primitives converge to probability-like structure.
Goals
goals- Derive an adaptive world-state architecture without starting from existing AI technology names, then test whether its differences survive implementation.
- Decide, falsifiably, between Distinct Advantage, Operational Convergence, Behavioral Equivalence Only, Inconclusive and Architecture Worse.
- Test the Probabilistic Appearance Convergence Conjecture (PACC) in fully observable micro-environments before touching language models.
Open questions
open_questions- PACC-A (architecture attractor) is not closed: only two independent convergent families exist under the preregistered redundancy rule.
- Reverse chart transport in the PACC atlas carries a persistent destination bias that neither a bounded quadratic transition nor a base-point residual field explains (v0.12–v0.13); v0.14 tests a sign-free residual subspace.
- AER-0 has no executable cross-runtime comparison yet: LangGraph could not be installed in the comparison environment (R2), and R7 (independent witness, transparency proof, signer rotation) is not started.
- The real-language-model PACC A/B/C benchmark has a validated harness but has never been executed with a real model.
Milestones
milestones- Adaptive Epistemic Systems Series papers 01–11 complete (canonical UTF-8 sources, SHA-256 manifest).
- Adaptive Epistemic AI Runtime technical whitepaper v0.1 with schemas, pseudocode and the AER-0 roadmap.
- AER-0 MVP v0.1 (Python + SQLite, 25 tests) and comparison rounds R1–R6 (79 tests at R6).
- PACC conjecture paper (2026-09-08) and PACC-Lab v0.1–v0.13.
- PACC-LLM Hybrid Lab v0.1 (synthetic A/B/C) and v0.2 (real-LLM harness, not yet executed).
Research lines and systems in this program
| Source | Relation | Target | Status | ID |
|---|---|---|---|---|
RES-2026-0001 Blind derivation of an adaptive epistemic architecture | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0001 |
RES-2026-0002 PACC conjecture — do non-probabilistic primitives converge to probability-like structure? | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0002 |
RES-2026-0003 Does epistemic governance survive implementation? The AER-0 architecture comparison | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0003 |
RES-2026-0004 A PACC-style runtime on language models: reasoning, intent and creative breadth | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0004 |
Recorded fields
limitations- Everything measured so far is synthetic data plus theoretical reasoning, or a deterministic scenario in a reference runtime. Until a real hybrid model exists, an inference is only an inference: theoretically possible is not actually possible.
Relations
| Source | Relation | Target | Status | ID |
|---|---|---|---|---|
RES-2026-0001 Blind derivation of an adaptive epistemic architecture | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0001 |
RES-2026-0002 PACC conjecture — do non-probabilistic primitives converge to probability-like structure? | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0002 |
RES-2026-0003 Does epistemic governance survive implementation? The AER-0 architecture comparison | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0003 |
RES-2026-0004 A PACC-style runtime on language models: reasoning, intent and creative breadth | belongs_to | PRG-2026-0001 Adaptive Epistemic Systems | ACTIVE | REL-2026-0004 |
History and provenance
- Canonical URL
- https://evemisslab.com/ai/programs/PRG-2026-0001/
- Machine-readable
/ai/programs/PRG-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