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Maintaining Equilibria During Exploration in Sponsored Search Auctions

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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 set of parameters which control the rate of exploration. These parameters 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.

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Authors and Affiliations

  1. Yahoo! Research, New York, NY, USA

    John Langford

  2. Department of Computer Science, Rutgers University, Piscataway, NJ, USA

    Lihong Li

  3. Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA

    Yevgeniy Vorobeychik & Jennifer Wortman

Authors
  1. John Langford
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  2. Lihong Li
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  3. Yevgeniy Vorobeychik
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  4. Jennifer Wortman
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Corresponding author

Correspondence to Jennifer Wortman.

Additional information

A preliminary version of this work appeared in the Third International Workshop on Internet and Network Economics [17]. Part of this work was done while J. Wortman, Y. Vorobeychik, and L. Li were visiting Yahoo! Research.

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Langford, J., Li, L., Vorobeychik, Y. et al. Maintaining Equilibria During Exploration in Sponsored Search Auctions. Algorithmica 58, 990–1021 (2010). https://doi.org/10.1007/s00453-009-9318-z

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  • DOI: https://doi.org/10.1007/s00453-009-9318-z

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