foxhunt

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jgrusewski eabc7ae36b feat: Phase 3 reward tuning — fix dynamics+architecture, search 7 reward dims

Three-phase hyperopt pipeline:
  Phase 1 (fast): fix architecture + reward, search dynamics (~17D)
  Phase 2 (full): fix dynamics, search architecture (~5D)
  Phase 3 (reward): fix dynamics + architecture, search reward weights (7D)

Phase 3 is the fastest (~10s/trial) since only experience collection
changes. CLI: --phase reward --hyperopt-params phase2_results.json

Argo template runs all 3 phases sequentially. Phase 2 writes to
_phase2_results.json, Phase 3 writes final _hyperopt_results.json.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-22 21:45:00 +01:00

baseline_common

fix(ml): wire spread_cost_bps into RL training — commission + spread = total tx cost

2026-03-01 22:10:43 +01:00

cuda_test.rs

fix: wire real GPU backprop + SPSA gradients, fix checkpoint loading, eliminate candle from examples

2026-03-20 15:41:42 +01:00

download_baseline.rs

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

evaluate_baseline.rs

fix: update evaluate_baseline for new backtest evaluator API