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Poster
Learning Prices for Repeated Auctions with Strategic Buyers
Kareem Amin · Afshin Rostamizadeh · Umar Syed

Thu Dec 05 07:00 PM -- 11:59 PM (PST) @ Harrah's Special Events Center, 2nd Floor #None
in Poster Session »

Inspired by real-time ad exchanges for online display advertising, we consider the problem of inferring a buyer's value distribution for a good when the buyer is repeatedly interacting with a seller through a posted-price mechanism. We model the buyer as a strategic agent, whose goal is to maximize her long-term surplus, and we are interested in mechanisms that maximize the seller's long-term revenue. We present seller algorithms that are no-regret when the buyer discounts her future surplus --- i.e. the buyer prefers showing advertisements to users sooner rather than later. We also give a lower bound on regret that increases as the buyer's discounting weakens and shows, in particular, that any seller algorithm will suffer linear regret if there is no discounting.

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Author Information

Kareem Amin (University of Pennsylvania)
Afshin Rostamizadeh (Google Research)
Umar Syed (Google Research)

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