16100912c3
Adds combined SP18 D-leg Hold-reward adaptive-cap slots [483..493) + B-leg TD(λ) Q(s') bootstrap diagnostics + PopArt reset flag at [493..505) per spec DD6 (D-leg 10 slots) + B-DD13 (B-leg 12 slots). D-leg [483..493) — 10 slots: 483 HOLD_REWARD_POS_CAP (sentinel 5.0, bounds [0.5, 50]) 484 HOLD_REWARD_NEG_CAP (sentinel -10.0) 485 HOLD_REWARD_DECOMP_DIAG (sentinel 0.0) 486 HOLD_OPP_COST_FIRE_RATE_EMA (sentinel 0.0) 487..493 HRC_* Welford accumulators (mirrors SP16 T3 HCS_* pattern) B-leg [493..505) — 12 slots: 493 TD_ERROR_MAG_EMA (HEALTH_DIAG B-DD9 ratio gate input) 494 Q_NEXT_TARGET_P99 (target-Q bootstrap bound check) 495 Q_NEXT_MINUS_REWARD_P99 (sanity: should be O(1) post-fix) 496 V_SHARE_TREND_DIAG (B-leg synergy probe) 497 POPART_RESET_FLAG (sentinel 1.0 — one-shot, B-DD11) 498..504 TDB_* Welford accumulators (mirrors HRC_* pattern) 504 RESERVED (B-leg follow-up) Pearl-A first-observation bootstrap sentinels match position-side SP14 P0-A REWARD_POS_CAP_ADAPTIVE pattern (POS=5.0, NEG=-10.0). Slot 497 POPART_RESET_FLAG sentinel = 1.0 per B-DD11 — host writes 1.0 once at first SP18 epoch, kernel zeroes after consuming, gating the per-fold PopArt slot 63 EMA reset at the SP18 deployment boundary. ISV_TOTAL_DIM bumped 483 → 505; layout_fingerprint_seed updated with all 22 new slot names; state_layout.cuh C-side mirror in lockstep (continues SP14-P0A/P1/audit-fix-4A/4B mirror precedent — SP16/SP17 slots intentionally not mirrored per existing pattern, only SP18 gets fresh mirror entries). `feedback_no_partial_refactor`: both legs share an ISV section + a single fingerprint bump; SP13 [380..383) and SP16 [461..474) slots remain ALLOCATED but RETIRED in PP.4 (sentinel 0.0, no producer launch — RESERVED-gap pattern from SP14-C.1 preserves checkpoint compatibility). Audit doc updated per Invariant 7 with Pre-Phase PP.2 entry. Spec: docs/superpowers/specs/2026-05-08-sp18-reward-shape-hold-attractor-design.md Plan: docs/superpowers/plans/2026-05-08-sp18-reward-shape-hold-attractor.md Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ml
10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
Models
- DQN (Rainbow) — deep Q-network with prioritized replay, dueling heads, noisy nets
- PPO — proximal policy optimization with GAE, LSTM policies, clip-higher
- TFT — temporal fusion transformer for multi-horizon forecasting
- Mamba2 — state space model for sequence prediction
- Liquid Networks — biologically inspired networks for non-stationary data
- TLOB — transformer-based limit order book analysis
- KAN — Kolmogorov-Arnold networks
- xLSTM — extended LSTM architecture
- TGGN — temporal graph neural network
- Diffusion — diffusion-based generative model
Key Modules
ensemble— model ensemble coordination and confidence aggregationhyperopt— PSO-based hyperparameter optimization with per-model adapterstrainers— unified training loops (DQN, PPO, supervised)inference—InferenceAdaptertrait for predictioncheckpoint— model checkpointing and restorationevaluation— walk-forward evaluation pipeline
Usage
use ml::dqn::DQN;
use ml::ppo::PpoTrainer;