Peter Stone
ABSTRACT
The First Trading Agent Competition (TAC) was held from June 22 to July 8, 2000. TAC was designed to create a benchmark problem in the complex domain of e-marketplaces and to motivate researchers to apply unique approaches to a common task. This paper describes \attac, the first-place finisher in TAC. \attac\ uses a principled bidding strategy that includes several elements of {adaptivity\/}. In addition to the success at the competition, isolated empirical results are presented indicating the robustness and effectiveness of \attac's adaptive strategy.
- 1.P. C.Cramton. The FCC spectrum auctions: An early assessment. Journal of Economics and Management Strategy, 6(3):431-495, 1997.Google Scholar
Cross Ref
- 2.J. A. Csirik, M. L. Littman, S. Singh, and P. Stone. FAucS: An FCC spectrum auction simulator for autonomous bidding agents. Under Review, 2001. Available at http: //www.research.att.com/~pstone/papers.html.Google ScholarCross Ref
- 3.A. Eisenberg. In online auctions of the future, it'll be bot vs. bot vs. bot. The New York Times, 2000. August 17th.Google Scholar
- 4.M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-completeness. Freeman, San Francisco, CA, 1979. Google ScholarDigital Library
- 5.A. Greenwald and P. Stone. Autonomous bidding agents in the trading agent competition. IEEE Computing, 2001. To appear. Available at http: //www.research.att.com/~pstone/papers.html. Google ScholarDigital Library
- 6.M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Proceedings of the Eleventh International Conference on Machine Learning, pages 157-163, San Mateo, CA, 1994. Morgan Kaufman.Google ScholarDigital Library
- 7.S. Singh, M. Kearns, and Y. Mansour. Nash convergence of gradient dynamics in general sum games. In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI), pages 541-548, 2000. Google ScholarDigital Library
- 8.P. Stone. Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer. MIT Press, 2000. Google ScholarDigital Library
- 9.R. J. Weber. Making more from less: Strategic demand reduction in the FCC spectrum auctions. Journal of Economics and Management Strategy, 6(3):529-548, 1997.Google ScholarCross Ref
- 10.M. P. Wellman, P. R. Wurman, K. O'Malley, R. Bangera, S.-d. Lin, D. Reeves, and W. E. Walsh. A trading agent competition. In press. Available at http://tac.eecs.umich.edu/reports.html, 2001.Google Scholar
Index Terms
- ATTac-2000: an adaptive autonomous bidding agent
Recommendations
ATTac-2000: an adaptive autonomous bidding agent
The First Trading Agent Competition (TAC) was held from June 22nd to July 8th, 2000. TAC was designed to create a benchmark problem in the complex domain of e-marketplaces and to motivate researchers to apply unique approaches to a common task. This ...
ATTac-2001: A Learning, Autonomous Bidding Agent
AAMAS '02: Revised Papers from the Workshop on Agent Mediated Electronic Commerce on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and SystemsAuctions are becoming an increasingly popular method for transacting business, especially over the Internet. This paper presents a general approach to building autonomous bidding agents to bid in multiple simultaneous auctions for interacting goods. The ...
Sincere and sophisticated players in the envy-free allocation problem
EC '13: Proceedings of the fourteenth ACM conference on Electronic commerceWe study the problem of allocating a collective endowment of n objects among n agents when monetary compensation is available. We require budget balance and assume complete information. We also assume that money is desirable and that no object is ...
Comments