Proof of Theorem 3.6, (III): once is zero it stays zero
ProvedStatefulPricing.thm_3_6_proof_IIIdynamic-resource-allocationonline-learningp2o-gran-per-chapterp2o-plan-paperp2o-strengthenedp2o-v1posted-pricingregret
Consider a run of the chasing oracle of Theorem 3.4 on a DRACC instance with arbitrary valuations, ties broken by an injective rank, a feasible target policy, any initial inventory and any outcome of the coins. If for some , then
Since means , there are no Missing rounds after that point.
Differences from the source:
- generalization: ties broken by the lexicographic order on → ties broken by an arbitrary injective rank on bundles; reason: every lexicographic order is induced by an injective rank, so the statement specializes to the source's
- encoding: random coins of the oracle, an inventory vector on → the coin outcomes are an arbitrary fixed sequence and an arbitrary function ; reason: the claim holds for every coin outcome; values off are never read
- encoding: resources , vectors indexed by , prices in → resources are a finite set of natural numbers, inventory vectors equal to off , price vectors with values in at every resource; reason: changes no demand set, payment or inventory
Preamble
import Mathlib import Definitions.Def_StatefulPricing_Instance import Definitions.Def_StatefulPricing_Chase set_option autoImplicit false open MeasureTheory ProbabilityTheory
Formal statement
namespace StatefulPricing
/-- **(III) of the proof of Theorem 3.6** (arXiv:2005.01869v2, p.10): "(III) if φ(t) = 0 for some
tinit ≤ t ≤ tfinal, then φ(t′) = 0 for all t < t′ ≤ tfinal."
For arbitrary valuations, ties broken by an injective rank, a feasible target policy, any initial
inventory and coin outcomes. -/
theorem thm_3_6_proof_III {T C W : ℕ} (c : Chase T C W) (hrank : Function.Injective c.rank)
(hγ : IsFeasiblePolicy c.γ) (tfinal : ℕ) :
∀ t, c.tinit ≤ t → t ≤ tfinal → c.phi t = 0 →
∀ t', t < t' → t' ≤ tfinal → c.phi t' = 0 := by sorry
end StatefulPricing
Source
Emek, Lavi, Niazadeh, Shi, Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes, arXiv:2005.01869v2, proof of Theorem 3.6, (III), p.10
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.