Phase E.1 Task 13. Same pipeline as the H=600 PASS run (cd5aa3402),
just `--horizon 6000` — the plan's production horizon. Result:
Q_SPREAD_EMA = 35.44 ≥ 0.05 PASS
ACTION_ENTROPY_EMA = 2.00 ≥ 1.099 PASS
RETURN_VS_RANDOM_EMA = +1.003σ ≥ 0.0 PASS
EARLY_Q_MOVEMENT_EMA = 0.130 ≥ 0.01 PASS
Overall: PASS (H=6000 scale-up VIABLE)
H=600 vs H=6000 side-by-side (same DQN, only horizon changed):
H=600 H=6000
rollout_R_mean -18 -236 (13× for 10× horizon — sublinear)
RETURN_VS_RANDOM_EMA +1.043σ +1.003σ (alpha signal generalizes)
Q_SPREAD_EMA 10.92 35.44 (sharper action discrimination)
EARLY_Q_MOVEMENT_EMA 0.099 0.130 (more weight movement per episode)
Overall PASS PASS
The Mamba2 K=6000 alpha-cache (config/ml/alpha_logits_cache.bin) was
directly trained for this horizon, so generalization at H=6000 is the
expected result. Confirmed empirically.
Runtime: 80s for 1000 episodes × 6000 steps = 6M transitions
(~75K transitions/sec, same throughput as H=600).
Milestone E.1 is now CLOSED with all kill criteria PASSING at the
production horizon. Per the plan, this unlocks Milestone E.2 — the
stacker-threshold ISV controller (engagement-rate self-correction).
Reproduction:
cargo run -p ml --release --example alpha_dqn_h600_smoke -- \
--fxcache-path .../9297....fxcache \
--alpha-cache config/ml/alpha_logits_cache.bin \
--horizon 6000 --n-episodes 1000 \
--max-snapshots 1500000
Verdict + per-checkpoint KC trajectory in config/ml/alpha_dqn_h6000_smoke.json.
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