64d0eb8bfe
compute_expected_q was called with null_atom_stats=0 (NULL pointer), so the kernel skipped atom entropy/utilization accumulation entirely. atom_stats_buf existed but was never passed. This disabled: - G4 adaptive gamma annealing (uses atom_utilization) - Homeostatic regularizer atom_util observable - ISV atom utilization signal Now passes atom_stats_buf.raw_ptr() with a cuMemsetD32 zero before each call (kernel uses atomicAdd). Also passes q_var_buf_trainer for per-action Q-variance computation. Co-Authored-By: Claude Opus 4.6 (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;