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Maintaining Equilibria During Exploration in Sponsored Search Auctions

By Jennifer Wortman, Yevgeniy Vorobeychik, Lihong Li and John Langford


Abstract. We introduce an exploration scheme aimed at learning advertiser click-through rates in sponsored search auctions with minimal effect on advertiser incentives. The scheme preserves both the current ranking and pricing policies of the search engine and only introduces one parameter which controls the rate of exploration. This parameter can be set so as to allow enough exploration to learn advertiser click-through rates over time, but also eliminate incentives for advertisers to alter their currently submitted bids. When advertisers have much more information than the search engine, we show that although this goal is not achievable, incentives to deviate can be made arbitrarily small by appropriately setting the exploration rate. Given that advertisers do not alter their bids, we bound revenue loss due to exploration.

Year: 2009
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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