Reference · The Applied Higher-Order Functions catalogue

rainbow.algorithms.proofs.ahof.agent-model

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

AHoF V3 Agent Model Construction: fit a model of another agent's behaviour; the model fits when its prediction error is within the tolerance: model-fits? error tolerance = decide (error <= tolerance). 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.agent-model` prints this classification.

agent-model/model-fits? :
  (x₁ x₂ : ℚ≥0)
  → data/Bool

agent-model/low-error-fits :
  → search/poll-improves 1/4 1/2 = data/true

agent-model/boundary-fits :
  → search/poll-improves 1/2 1/2 = data/true

agent-model/fit-certificate :
  → 1/4 ≤ 1/2

agent-model/high-error-misfits :
  → search/poll-improves 3/4 1/2 = data/false