# Эксперимент: Adaptive Zonotope Safety Shield (#1087)

{
  "worked": true,
  "confidence": 8,
  "verdict": "Built and numerically verified an adaptive axis-aligned disturbance zonotope shield with affine reachability and online median/max-radius updates. The mechanism manifested: zonotope box containment had 0 disagreements over 3000 cases, learned q tracked disturbance amplitude plus epsilon within 0.00292, and a disturbance jump expanded q in the first batch with 100% coverage. However, the tiny shield comparison showed no efficiency or safety win: adaptive rejection was 70.08% versus fixed 66.86%, with violation rates 67.49% versus 66.86%.",
  "metrics": {
    "baseline": "Fixed disturbance box: rejection_rate=0.6686, violation_rate=0.6686",
    "idea": "Adaptive disturbance box: rejection_rate=0.7008, violation_rate=0.6749; scaling q maximum absolute error=0.0029165, minimum held-out coverage=1.0; jump q=0.10362 to 0.31315 in one batch"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 adaptive_shield_experiment.py",
  "files": [
    "adaptive_shield_experiment.py",
    "results.json"
  ],
  "limitations": "This is a deterministic toy affine point-mass experiment, not PPO or a learned nonlinear dynamics model. It uses axis-aligned disturbance generators, a zero-action backup, short finite episodes, and does not test multi-step reachability, calibration under distribution shift beyond one jump, computational overhead, or statistically repeated seeds."
}