Mechanisms for Selling an Item Among a Strategic Bidder and a Profiled Agent

Ioannis Caragiannis, Georgios Kalantzis

Abstract: We consider a scenario where a single item can be sold to one of two agents. Both agents draw their valuation for the item from the same probability distribution. However, only one of them submits a bid to the mechanism. For the other, the mechanism receives a \textit{prediction} for her valuation, which can be true or false. Our goal is to design mechanisms for selling the item which make as high revenue as possible in cases of a correct or incorrect prediction. As benchmark for proving our revenue-approximation guarantees, we use the maximum expected revenue that can be obtained by a strategic and a honest bidder. We study two mechanisms. The first one yields optimal revenue when the prediction is guaranteed to be correct and a constant revenue approximation when the prediction is incorrect, assuming that the agent valuations are drawn from a monotone hazard rate (MHR) distribution. Our second mechanism ignores the prediction for the second agent and simulates the revenue-optimal mechanism when no bid information for the bidders is available. We prove, again assuming that valuations are drawn from MHR distributions, that this mechanism achieves a constant revenue approximation guarantee compared to the revenue-optimal mechanism for a honest and a strategic bidder. The MHR assumption is necessary; we show that there are regular probability distributions for which no constant revenue approximation is possible.