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An Adaptive Proportional Value-per-Click Agent for Bidding in Ad Auctions

  • Kyriakos C. Chatzidimitriou
  • Lampros C. Stavrogiannis
  • Andreas L. Symeonidis
  • Pericles A. Mitkas
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 119)

Abstract

Sponsored search auctions constitutes the most important source of revenue for search engine companies, offering new opportunities for advertisers. The Trading Agent Competition (TAC) Ad Auctions tournament is one of the first attempts to study the competition among advertisers for their placement in sponsored positions along with organic search engine results. In this paper, we describe agent Mertacor, a simulation-based game theoretic agent coupled with on-line learning techniques to optimize its behavior that successfully competed in the 2010 tournament. In addition, we evaluate different facets of our agent to draw conclusions about certain aspects of its strategy.

Keywords

sponsored search advertisement auction trading agent game theory machine learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kyriakos C. Chatzidimitriou
    • 1
  • Lampros C. Stavrogiannis
    • Andreas L. Symeonidis
      • 1
    • Pericles A. Mitkas
      • 1
    1. 1.Informatics and Telematics InstituteCentre for Research and Technology HellasGreece

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