805a7429f4
Kernel signature reduced from 9 to 6 args; pearl_2_budget_update now writes only budget_iqn[4] and flatness[4]. Launcher migrated atomically: arg list shrinks, apply_pearls smoothing loop shrinks from 5 slot-blocks to 2. SCRATCH_PEARL_2_C51, SCRATCH_PEARL_2_CQL, SCRATCH_PEARL_2_ENS deleted as orphan constants per feedback_wire_everything_up. The corresponding producer scratch slots (111..115, 119..127) become reserved-for-future inside the buffer. CQL/C51/ENS budget ownership now lives in the SP7 loss-balance controller (loaded in T5; wired in T7). 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;