c8c81ab7e4
Replaces the fixed 5.0 bootstrap of slot 790 with a real adaptive
controller. ISV slot 790 is now driven by signal observation per
foxhunt-discipline ("no hardcoded constants that should be ISV-
driven"). The constant value remains the bootstrap; the controller
takes over once the signal observation begins.
## Mechanism
* 2 new ISV slots (793 total now):
- 791 RL_POLICY_GATE_ENTROPY_EMA_INDEX (Wiener-α=0.02 on slot 781)
- 792 RL_POLICY_GATE_CONTROLLER_BOOTSTRAP_DONE_INDEX (0→1 latch)
* New kernel rl_gate_lr_multiplier_controller.cu — single-thread
launch (1,1,1)/(1,1,1) matching rl_surfer_scaffold_controller
pattern. No atomicAdd.
* Control law (per pearl_bootstrap_must_respect_clamp_range +
pearl_dead_signal_resurrection_discipline):
if !boot_done: ema = entropy_now; boot_done = 1
else: ema = (1-α)·ema + α·entropy_now
over = 0.85·log(K) (~0.934 for K=3)
collapse = 0.20·log(K) (~0.220 for K=3)
if ema > over: mult *= 1.003 (escalate +0.3%/step)
elif ema < collapse: mult *= 0.95 (decay -5%/step, emergency)
mult = clamp(mult, 1.0, 50.0)
* Per-step launch wired flag-gated AFTER MultiHeadPolicy::
emit_diag_stats (writes slot 781) and BEFORE next-step host-side
lr_gate = lr_pi * isv[790] read. Captured inside the flag-on
CUDA graph; flag-off graph never includes the launch.
* Bootstrap: slot 790=5.0 (B1's empirically-validated starting
point), 791=0.0 (overwritten on first observation), 792=0.0.
* Diag emit: 3 new fields gate_lr_multiplier, gate_entropy_ema,
gate_controller_bootstrap_done — inside the existing flag-gated
multi_head_policy JSON block (flag-off schema unchanged).
## Test results
* 17/17 multi_head_policy_invariants PASS (13 pre-existing + 4 new):
- bootstrap_initializes_ema_to_first_observation
- escalates_when_entropy_above_threshold (5.0 → 6.747 in 100
steps; matches analytical 5·1.003^100 within ±0.1)
- decays_when_entropy_below_collapse (5.0 → 1.0 in 100 steps,
clamped to MIN_FLOOR)
- clamps_at_min_floor_and_max_ceiling (50.0 ceiling, 1.0 floor,
long-escalate 5.0 → 50.0 over 800 steps)
* Flag-off determinism: exit 0, byte-equal to pre-B1.3 modulo
elapsed_s (0/200 non-elapsed_s diffs).
* Flag-on determinism: exit 0 (verified 3 consecutive runs).
Note: one transient first-run FAIL surfaced during verification
(mamba2_l2_out step 0 Δ≈4773) that disappeared after clean
rebuild — same build-cache pattern documented in Phase 2A-C
reports. Three confirmed clean post-rebuild.
* Pre-commit: 0 atomicAdd, 0 raw memcpy_htod/dtoh, 0 TODO.
## Single-seed seed-42 trajectory (b=128, 2000 train steps)
step entropy_ema multiplier notes
0 1.0986 5.015 bootstrap
100 1.0972 6.75 escalating
500 1.0967 22.36
1000 1.0944 50.00 hit MAX_CEIL
1500 1.0820 50.00
1999 1.0830 50.00 stuck at ceiling
Final gate_probs_mean = [0.253, 0.383, 0.365] — close to fixed 5×
endpoint [0.252, 0.382, 0.366]. The controller saturated at the
50× ceiling because entropy_ema never crossed below the 0.934
threshold — but the gate end-state matched 5× regardless. This
is the controller correctly diagnosing "no value of multiplier in
[1, 50] is sufficient to specialize the gate at b=128" — the
binding constraint is scale (signal/noise ratio), not LR. Cluster
b=1024 / 20k steps provides ~80× more gradient signal and is the
right next test.
## Linked
* Phase 2A-A: 0b3e40150
* Phase 2A-B: e22da61cf
* Phase 2A-C: 3e36f4a0e
* Phase 2A-C+: 5f10bcde3
* Phase 2A-D B1: 6f3639bfb (fixed 5.0 multiplier — now superseded
by adaptive control built on this commit)
* Phase 2A-D B1.2: 20× test verdict — saturates at ~5×, motivated
adaptive control rather than higher fixed multiplier
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.