grid-policy-mlp-repaired-v3

PPO-trained GridPolicyMLP after analytic parameter repairs from KimiBrainSurgery. Architecture: 500 β†’ 32 β†’ 32 β†’ 5, tanh, 17,253 parameters. W2 solvers use analytic derivatives and local linearization; these repairs do not run gradient-descent training. Gates measure finite sets, not universal safety.

Frozen paired evaluation β€” greedy actions

Games Seeds Original mean v3 mean Paired gain Wins / losses / ties
1,000 20000–20999 8.694 10.528 +1.834 137 / 17 / 846

v1/v3 use the same old set; v1's 1,000-game result includes its earlier 64-game pilot. Seventeen v3 failures informed v4 development. v4's old-set mean is 12.182 versus original 8.694; its separate fresh-set result appears above for v4. Zero observed v1 losses is not a never-worse guarantee. v3 and v4 have higher measured means but observed regressions, including the ascent pre-positioning class. These numbers do not estimate sampled-action play or the separate Qwen experiment.

The original v1 loop kept three of four edits because mean return on a reused 64-game gate did not decrease. Only one kept edit reports its targeted state fixed.

Current repair status

Experiment 8 tested 18 batch configurations against seven failure states under v4. None fixed all seven while preserving gate mean; no v5 was promoted. A candidate fixed one state at equal gate mean, but failed that all-seven requirement. This is a negative result for tested solvers, not proof that a larger network is necessary. Some former v4 fresh-set loss seeds now enter batch mining: future candidates need a new untouched final audit. The historical frozen v4 evaluation is unchanged. Batch evidence and limits.

Checkpoint and reproduction

policy_weights.npz contains float32 W1, b1, W2, b2, W3, b3. File SHA-256: e6d3e453a9c74efb0cd2c017713afe3c916dbdaeb16a7113d8d79c9f7a33af94. Documentation synchronization did not alter these weights. Current evidence and status Β· Per-seed dataset Β· Live visualizer.

Independent work inspired by Sparks of Weight-Space Programming. Different policy provenance and repair protocols must be evaluated separately.

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