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Poster

Revenue Optimization against Strategic Buyers

Mehryar Mohri · Andres Munoz

210 C #91

Abstract: We present a revenue optimization algorithm for posted-price auctions when facing a buyer with random valuations who seeks to optimize his γ-discounted surplus. To analyze this problem, we introduce the notion of epsilon-strategic buyer, a more natural notion of strategic behavior than what has been used in the past. We improve upon the previous state-of-the-art and achieve an optimal regret bound in O(logT+1log(1/γ)) when the seller can offer prices from a finite set \cP and provide a regret bound in O~(T+T1/4log(1/γ)) when the buyer is offered prices from the interval [0,1].

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