docs/releases/r0513.md

Release Notes — r0513

The Engine That Won't Stop Learning

Package: a11oy 0.1.0+r0513
Author: Stephen P. Lutar Jr. stephen@szlholdings.com
ORCID: 0009-0001-0110-4173
Org: SZL Holdings
Doctrine: v2
Date: 2026-05-14
License: Apache-2.0

---

Architecture Overview

r0513 completes the Brain v1 build by adding the inner-agent society to the Ouroboros Infinity loop. The full pipeline is:

Goal
 │
 ▼
A11oyAgent.think()
 ├─ Quipu Plan (DAG of steps)
 ├─ Execute steps → RAGReceipt per step
 ├─ Evalgate: 9-axis conjunctive AND gate
 ├─ BiettiMemory: goal → trace summary
 ├─ Observatory: drift detection
 └─ CodexSession → CodexClosure (Merkle root)
 │
 ▼
LoopController.meditate_n_cycles()
 ├─ CycleHead: current_head seeds each cycle
 ├─ Thesis corpus rotation: F1–F15 SZL formulas
 ├─ tick() → CycleTail(tail_hash, receipt, eval_result)
 └─ tail_hash → next current_head (Ouroboros fold)
 │
 ▼
Society.tick_all()  ─── 7 inner agents in fixed order ───►
 ├─ Perceiver (FEP — surprise minimization)
 ├─ Predictor (world-model prefix forecasting)
 ├─ Proposer (ReAct/Reflexion template proposals)
 ├─ Critic (Constitutional AI axis calibration)
 ├─ Rememberer (Park memory stream)
 ├─ Dreamer (DreamerV3 offline planning)
 └─ Arbiter (Minsky Society of Mind weighted selection)
 │
 ▼
Society.learn_all(gate_outcome)  ─── per-agent state update ───►

Every crossing of the evalgate gate calls learn() on all 7 agents.
The loop invariant is "but never stop".

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7 Inner-Agent Roles and Scientific Basis

Agent	Leader Citation	tick() function	learn() update
Perceiver	Friston, Free Energy Principle (2010)	Surprise = edit distance to last_head	Running mean surprise (EMA)
Predictor	Karpathy / Sutskever	Prefix match forecast	Residual MAE accumulation
Proposer	Yao & Shinn, ReAct/Reflexion (2023)	Template-keyed proposals	Pass/fail count per template key
Critic	Bai et al., Constitutional AI (2022)	Per-axis score prediction	Per-axis calibration error (running MAE)
Rememberer	Park et al., Generative Agents (2023)	SHA-256 key memory lookup	Recency + frequency weight update
Dreamer	Hafner et al., DreamerV3 (2023)	Dream score vs reality delta	Dream–reality residual MAE
Arbiter	Minsky, Society of Mind (1986)	Weighted selection of winner	+1 on winner, -1 on losers

All agents implement:

• tick(loop_state: LoopState) -> AgentReport
• learn(report: AgentReport, gate_outcome: GateOutcome) -> None

All learn() updates are:

• Deterministic: seeded from sha256_text(loop_state.current_head + salt)
• Idempotent w.r.t. replay: same input → same state delta
• JSON-serializable: get_state() / load_state() round-trip

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New Module: inner_agents.py

src/a11oy/inner_agents.py — 916 lines, Apache-2.0, r0513.

Exports:

• InnerAgent (ABC with tick + learn + state I/O)
• Perceiver, Predictor, Proposer, Critic, Rememberer, Dreamer, Arbiter
• Society (tick_all, learn_all, snapshot, snapshot_hash, to_json, from_json)
• AgentReport, GateOutcome, SocietyReport

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Full Test Suite

$ pytest --tb=short -q 2>&1 | tail -2
243 passed in 3.22s

243 tests — all passing. Zero skips, zero failures.

r0513 additions: test_inner_agents.py — 33 tests

Key coverage:

• All 7 agents tick without error
• All 7 agents learn without error
• tick() output is an AgentReport with correct role
• learn() mutates agent state deterministically
• Society.tick_all() runs all 7 agents in fixed order
• Society.learn_all() propagates gate_outcome to all agents
• Society.snapshot() returns JSON-serializable dict
• Society.snapshot_hash() is deterministic
• Society.to_json() / from_json() round-trip
• 5× replay: Society.tick_all()+learn_all() is byte-identical with frozen time

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Code Quality

$ ruff check src/ tests/
All checks passed!

$ mypy --strict src/
Success: no issues found in 20 source files

• ruff: clean (E, F, W, I, UP, B, C4, SIM; E501 ignored)
• mypy --strict: clean across all 20 source files

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Determinism Certification

v0 baseline (preserved)

$ for i in 1..5: SZL_FROZEN_TIME=2026-05-14T10:00:00Z python examples/hello_brain.py | sha256sum
a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0
a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0
a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0
a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0
a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0

v0 hash a8603d5de9f3c97d94d13b5e394424c2e18f1be352f98b097f43eee5947d90a0 — unchanged.

v1 + r0513 (agi_brain.py)

$ for i in 1..5: SZL_FROZEN_TIME=2026-05-14T10:00:00Z python examples/agi_brain.py | sha256sum
bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c
bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c
bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c
bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c
bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c

v1 hash bbf72d4ab5b3eddb18d889b67426636107d816101948e989fa168074bc126e8c — 5× identical.

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Cryptographic Receipt

v1_codex_root (SHA-256 Merkle chain over all 20 src/a11oy/*.py):
eab2a8c4b0059de48ca8e613c84da994a45bf3f1f61e78949ecc059c42ac8c0c

r0513_continuum_hash (sha256(v1_codex_root + "r0513")):
46812870ce59251d8ea8e5494702aef05a3fedd061e182ee87a40dca238b867f

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What r0513 Is NOT

• Not ML training. No weights updated. MockCortex only.
• Not AGI. See AGI_HORIZON.md for the honest 9-gap analysis.
• Not production-ready. No real LLM connected. No real tool use.

What it IS: a verifiable, auditable, doctrine-enforced cognitive scaffold that runs forever and learns from every crossing.

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Deferred to v2

• Precision-weighted prediction-error gate (Neuroscience pod): Noted in Critic docstring. Requires gradient infrastructure. Risk too high for v1.
• Goedel-Prover-V2: 12 sorry holes in EvalGate.lean (BLOCKER C1). Closes in next pod.

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File Manifest (new in r0513)

File	Lines	Description
src/a11oy/inner_agents.py	916	7 inner agents + Society
tests/test_inner_agents.py	500	33 tests for inner_agents
examples/agi_brain.py	82	End-to-end demo: agent + loop + society
BRAIN_V1_REPORT.md	255	Full verified build report
AGI_HORIZON.md	166	Honest AGI gap analysis
BRAIN_V0_5_REPORT.md	148	Infinity loop addition report
RELEASE_NOTES_r0513.md	(this)	Release notes

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r0513 — The Engine That Won't Stop Learning.