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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
PwC: IAB U.S. Internet Advertising Revenue Report for 2009 (April 2010)
Jansen, B.J., Mullen, T.: Sponsored search: an overview of the concept, history, and technology. International Journal of Electronic Business 6(2), 114–131 (2008)
Jordan, P.R., Cassell, B., Callender, L.F., Kaul, A., Wellman, M.P.: The ad auctions game for the 2010 trading agent competition. Technical report, University of Michigan, Ann Arbor, MI 48109-2121 USA (2010)
Vorobeychik, Y.: A Game Theoretic Bidding Agent for the Ad Auction Game. In: Third International Conference on Agents and Artificial Intelligence, ICAART 2011 (January 2011)
Feldman, J., Muthukrishnan, S.: Algorithmic methods for sponsored search advertising. In: Liu, Z., Xia, C.H. (eds.) Performance Modeling and Engineering (2008)
Das, A., Goitis, I., Karlin, A.R., Mathieu, C.: On the effects of competing advertisements in keyword auctions. Working Paper (2008)
Pardoe, D., Chakraborty, D., Stone, P.: TacTex09: A champion bidding agent for ad auctions. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) (May 2010)
Berg, J., Greenwald, A., Naroditskiy, V., Sodomka, E.: A knapsack-based approach to bidding in ad auctions. In: Proceeding of the 2010 Conference on ECAI 2010: 19th European Conference on Artificial Intelligence, pp. 1013–1014. IOS Press, Amsterdam (2010)
Cigler, L., Mirza, E.: EPFLAgent: A Bidding Strategy for TAC/AA. Presentation in Workshop on Trading Agent Design and Analysis (TADA), ACM EC 2010 (July 2010)
Mansour, Y., Schain, M.: TAU Agent. Presentation in Workshop on Trading Agent Design and Analysis (TADA), ACM EC 2010 (July 2010)
Munsey, M., Veilleux, J., Bikkani, S., Teredesai, A., De Cock, M.: Born to trade: A genetically evolved keyword bidder for sponsored search. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8 (2010)
Chang, M., He, M., Luo, X.: Designing a successful adaptive agent for tac ad auction. In: Proceeding of the 2010 Conference on ECAI 2010: 19th European Conference on Artificial Intelligence, pp. 587–592. IOS Press, Amsterdam (2010)
Lahaie, S.: An analysis of alternative slot auction designs for sponsored search. In: EC 2006: Proceedings of the 7th ACM Conference on Electronic Commerce, pp. 218–227. ACM, New York (2006)
Jordan, P.R.: Practical Strategic Reasoning with Applications in Market Games. PhD thesis, University of Michigan, Ann Arbor, MI (2010)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
Vorobeychik, Y.: Simulation-based game theoretic analysis of keyword auctions with low-dimensional bidding strategies. In: Twenty-Fifth Conference on Uncertainty in Articial Intelligence (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chatzidimitriou, K.C., Stavrogiannis, L.C., Symeonidis, A.L., Mitkas, P.A. (2013). An Adaptive Proportional Value-per-Click Agent for Bidding in Ad Auctions. In: David, E., Robu, V., Shehory, O., Stein, S., Symeonidis, A. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC TADA 2011 2011. Lecture Notes in Business Information Processing, vol 119. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34889-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-34889-1_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34888-4
Online ISBN: 978-3-642-34889-1
eBook Packages: Computer ScienceComputer Science (R0)