Reference · The Applied Higher-Order Functions catalogue

rainbow.algorithms.proofs.ahof.disturbance-falsification

The Applied Higher-Order Functions cataloguesrc/rainbow/algorithms/proofs/ahof/disturbance_falsification.clj1 definitions, 4 theorems

AHoF V10 Disturbance-Based Falsification: search bounded disturbances to drive the system to a violation; a violation is found when the achieved robustness drops to or below the margin: violation? robustness margin = decide (robustness <= margin). Proved native and axiom-free (decision, two positive instances, at-most certificate, negative instance). Requires audit/decide-nnrat-at-most, nnrat/at-most, nnrat/decide-at-most-true-sound (all in the D63 checkpoint). Scope (measured by the kernel): this module has 4 worked instances (statements about specific values). None of its theorems is a guarantee about the algorithm for all inputs; `lein verify rainbow.algorithms.proofs.ahof.disturbance-falsification` prints this classification.

dist-fal/violation? :
  (x₁ x₂ : ℚ≥0)
  → data/Bool

dist-fal/low-robustness-violation :
  → ce-is/elite? 1/4 1/2 = data/true

dist-fal/boundary-violation :
  → ce-is/elite? 1/2 1/2 = data/true

dist-fal/robustness-certificate :
  → 1/4 ≤ 1/2

dist-fal/high-robustness-safe :
  → ce-is/elite? 3/4 1/2 = data/false