74eba7920e
Added select_action_inference(&self) — pure greedy forward pass with no exploration mutations (epsilon, noisy nets, count bonus, step counter are all skipped). Returns (FactoredAction, f32) where confidence is softmax probability of the selected action, clamped [0.5, 0.95]. Also added select_action_with_confidence(&mut self) for training path with the same confidence computation. Production wrapper now uses read lock (was write lock), enabling concurrent predictions. Confidence is real softmax probability instead of hardcoded 0.85. 323 trading_service tests, 15 DQN core tests, 0 clippy. Co-Authored-By: Claude Opus 4.6 <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;