Phase 1: Remove 5 DQNConfig boolean flags (use_soft_updates, use_iqn,
enable_q_value_clipping, use_cvar_action_selection, use_count_bonus).
All features now unconditionally active — no dead toggle branches.
Phase 2: Add spectral decoupling (L2 on Q-value logits, Pezeshki 2021)
and manifold mixup (Beta-sampled distribution interpolation with atomic
barrier sync) directly in C51 CUDA loss kernel. Zero CPU involvement.
Phase 3: Tag Experience transitions with market regime (ADX/CUSUM GPU
classifier kernel). Add regime-biased PER sampling via rejection with
IS weight correction. Decay factor controls cross-regime bleeding.
Phase 4: 6 family intensity scalars for hyperopt (adversarial,
regularization, augmentation, loss shaping, ensemble, causal). Scales
34 generalization params through 6 PSO dimensions instead of 34.
Search space: 24D → 30D (families additive, individual params kept).
20 files changed, +563/-69 lines. Full workspace compiles clean.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add backticks to type names in doc comments (doc_markdown)
- Mark eligible functions as const fn (missing_const_for_fn)
No behavior changes.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Move 53 DQN source files + gpu_replay_buffer from ml into standalone
ml-dqn crate. The ml crate's dqn module is now a thin re-export layer
(`pub use ml_dqn::*`) plus two bridge files (trainable_adapter.rs,
stress_testing.rs) that depend on ml-internal types.
Key changes:
- ml-dqn: 45 modules, 334 tests, compiles standalone
- ml: depends on ml-dqn, re-exports via dqn/mod.rs
- DQN.config: pub(crate) → pub for cross-crate access
- DQNAgent checkpoint methods moved into ml-dqn
- gpu_replay_buffer moved from cuda_pipeline/ to ml-dqn
- 8 dead-code files removed (never declared in mod.rs)
Net: -30,648 lines from ml crate. Workspace: 0 errors.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
