aa5908aa53
12 contiguous slots reserved for durable alpha-system infrastructure: - 539-542: diagnostics (Q-spread, action entropy, return-vs-random, early-Q-movement EMAs) — read by Phase E kill criteria - 543-546: stacker-threshold controller (threshold, target, observed-rate, Kelly attenuation) — engagement-rate self-correction - 547-548: random-uniform baseline (mean, std) — anchor for kill criterion 541 - 549-550: reserved spare (absorb growth without bumping ISV_TOTAL_DIM) Named `alpha_isv_slots` rather than `phase_e_isv_slots` because these slots are intended to outlive any individual Phase E/F/G milestone — the SP4..SP22 naming was iteration-scoped, but this block is system-scoped infrastructure. ISV_TOTAL_DIM bumped to 551. All indices validated in 4 unit tests (bounds, membership, uniqueness, total-dim coverage). Audit doc docs/isv-slots.md updated per Invariant-7.
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;