Repeated Contextual Auctions With Strategic Buyers

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 27 (NIPS 2014)(2014)

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摘要
Motivated by real-time advertising exchanges, we analyze the problem of pricing inventory in a repeated posted-price auction. We consider both the cases of a truthful and surplus-maximizing buyer, where the former makes decisions myopically on every round, and the latter may strategically react to our algorithm, forgoing short-term surplus in order to trick the algorithm into setting better prices in the future. We further assume a buyer's valuation of a good is a function of a context vector that describes the good being sold. We give the first algorithm attaining sublinear ((O) over tilde (T-2/3)) regret in the contextual setting against a surplus-maximizing buyer. We also extend this result to repeated second-price auctions with multiple buyers.
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