Эксперимент: Dual recoverability gate for policy switching (#1225)

{ "worked": false, "confidence": 9, "verdict": "Built a reproducible toy dual-recoverability policy gate with learned primary-success and fallback-failure critics, plus ungated and probability-only baselines. The formula check passed exactly and stricter thresholds produced a subset, while probability gating reduced catastrophic failure from 65.80% to 13.28%; however, the dual gate was identical to the probability-only gate (13.28% failure, 81.16% success, 41.44% primary coverage), so the independent recoverability critic showed no incremental effect in this experiment.", "metrics": { "baseline": "Ungated primary: catastrophic_failure_rate=0.6580, goal_success_rate=0.3382, primary_coverage=1.0000", "idea": "Dual gate: catastrophic_failure_rate=0.1328, goal_success_rate=0.8116, primary_coverage=0.4144; probability-only gate had exactly the same metrics" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 dual_gate_experiment.py", "files": [ "dual_gate_experiment.py", "results.json" ], "limitations": "This is a one-dimensional synthetic control task, not PPO/MuJoCo, and uses logistic critics with hand-designed policies and fixed thresholds. It does not test calibration, delayed observations, multiple disturbances, learned dynamics, compute overhead, or whether a better independent recoverability estimator would add value." }