chunker_phase1_v2

chunker_phase1_v2 — Schmidhuber chunker Phase 1, run 2 (DQ)

Result: DQ at 0.5621 acc / 13,936 J. Below floor by 13.8pp.

Changes from v1:

• H_MODEL_DIM: 192 → 256 (match alpha_06 NN capacity)
• H_MAX_LEN: 512 → 1024
• H_N_STEPS: 800 → 1200
• TAU: 0.30 → 0.15 (target p_s ~ 0.20; actual p_s = 0.3084)
• ALPHA: 0.50 → 0.60 (no surprise gating at inference)

Hypothesis was wrong. Capacity wasn't the limiter; the surprise-gated inference mix WAS. Removing it destroyed the architecture: a larger NN trained on a SMALLER subset (30.8% vs 43.5%) gets pushed toward overfitting hard examples, and ALPHA=0.6 makes it dominant on easy bytes where it has no training signal.

Critical finding for the chunker paradigm: v1's surprise-gated inference mix (if KN.max>=1-tau: 0.85*KN+0.15*NN else: 0.5*NN+0.5*KN) is essential.

Status: DQ. Stayed in adaptive-budget rule (3-run budget).