Port factorized Gaussian noise exploration and 51-atom categorical value
distribution to the CUDA experience collection kernel, fixing a correctness
bug where GPU Q-values were wrong when use_distributional=true (production
default) due to misinterpreted distributional weight shapes.
- D5: NoisyNet factorized noise (Box-Muller + f(x)=sign(x)*sqrt(|x|)) on
all 6 dueling layers, online network only — target stays deterministic
- D6: C51 distributional dueling forward with per-action atom softmax,
RMSNorm after shared/value/advantage layers, correct [51,128]/[255,128]
weight interpretation
- RmsNormWeightSet extraction and post-epoch sync (GPU-to-GPU)
- Fix get_effective_epsilon() to report actual 2% noisy floor instead of 0.0
- Proportional diversity entropy penalty (continuous gradient vs cliff)
- 2758 tests passing, 0 failures
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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