Appendix A.3, p. 18 — raising a policy value to the cost threshold
ProvedStrategicPolicy.MonotoneBinary.appendix_a3_second_casebest-responsedecision-policyoutcome-monotonicityp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1strategic-classification
Let be an optimal outcome monotonic policy under an additive, outcome monotonic cost. Choose an index with that is the highest-outcome index violating the binary rule (9); write . Suppose
Define by replacing only with . Then
This is the second improvement case used in Appendix A.3 to reach a binary policy.
Formalization Note The first relevant violator condition excludes earlier violations of either case of (9) above . The restriction follows the domain of (9). The standing model assumes distinct outcomes and the disclosed readings of (1) and additivity.
Preamble
import Mathlib import Definitions.Def_StrategicPolicy_MonotoneBinary_Setting
Formal statement
namespace StrategicPolicy.MonotoneBinary
variable {m : ℕ}
theorem appendix_a3_second_case [NeZero m]
(p q : Fin m → ℝ) (γ : ℝ) (c : Fin m → Fin m → ℝ)
(hstanding : Standing p q γ c) (hcost : OMCost q c)
(hadd : AdditiveCost q c)
(πstar : Fin m → ℝ) (hopt : Optimal p q γ c πstar)
(hmono : OMPolicy q πstar)
(i j : Fin m) (hprev : j.val + 1 = i.val) (hgain : γ < q i)
(hhighest : HighestViolator γ c q πstar i)
(hcase : πstar i < πstar j - c i j) :
u p q γ c πstar ≤
u p q γ c (Function.update πstar i (πstar j - c i j)) := by sorry
end StrategicPolicy.MonotoneBinary
Source
Tsirtsis et al., Optimal Decision Making Under Strategic Behavior, arXiv:1905.09239v5, p. 18, Appendix A.3, second case after the setup of the highest-outcome violator
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.