a92abedbae
LB_DIFF_VAR_CQL_BASE=297, LB_SAMPLE_VAR_CQL_BASE=301, LB_DIFF_VAR_C51_BASE=305, LB_SAMPLE_VAR_C51_BASE=309. Bumps SP5_SLOT_END 297 → 313 and SP5_PRODUCER_COUNT 123 → 139. Helper fns mirror the existing budget_*/flatness/q_var_per_branch pattern. Layout fingerprint extended. slot_layout_no_overlaps_and_total_correct asserts the new total. Audit doc Fix 31 stub added; will be extended commit-by-commit through Tasks 2-9 of the SP7 plan. 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;