jgrusewski 17d94e654c feat(dqn): Wave 10 - Architectural improvements and bug fixes ...

Wave 10 Summary:
- A1-A4: Architecture upgrades (4x network, LeakyReLU, Xavier init, diagnostics)
- A5-A6: Integration testing and production validation
- A7: Research hyperopt vs manual tuning (manual recommended)
- A8-A12: HOLD penalty tuning and critical bug fixes

Architecture Changes:
- Network expansion: [128,64,32] → [256,128,64] (2.5x parameters)
- LeakyReLU activation (alpha=0.01) to prevent dead neurons
- Xavier/Glorot initialization for better gradient flow
- Real-time diagnostic monitoring (Q-values, dead neurons, gradients)

Critical Bugs Fixed:
- Bug #1: HOLD penalty not wired to reward calculation
- Bug #2: Zero price error in calculate_hold_reward (velocity-based fix)
- Huber loss default enabled (Wave 9)
- Shape mismatch fix (Wave 8)

Test Results:
- Integration tests: 149/152 passing (98%)
- New tests: 40+ tests added across 15 files
- Xavier init: 5/5 tests passing
- HOLD penalty wiring: 4/4 tests passing
- Zero price fix: 4/4 tests passing

Known Issues:
- HOLD bias persists at ~100% despite penalties
- Gradient collapse: 217 instances per training run (norm=0.0)
- Reversed penalty effect: Higher penalties → worse Q-spread
- Root cause: Gradient clipping bottleneck (max_norm=10.0 vs penalty signal)

Phase 1 Trials (all completed without crashes):
- Penalty 0.5: Q-spread 250 pts, HOLD 100%
- Penalty 1.0: Q-spread 251 pts, HOLD 100%
- Penalty 2.0: Q-spread 255 pts, HOLD 100% (+ Q-value explosion)

Next Steps: Architectural investigation via parallel agent debugging

🤖 Generated with Claude Code (https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-11-06 00:38:23 +01:00

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