Abstract
An approach to auctions and bidding is founded on observations and expectations of the opponents’ behavior and not on assumptions concerning the opponents’ motivations or internal reasoning. A bidding agent operates in an information-rich environment that includes real-time market data and data extracted from the World Wide Web. This agent employs maximum entropy inference to determine its actions on the basis of this uncertain data. Maximum entropy inference may be applied both to multi-issue and to single-issue negotiation. Multi-issue variants of the four common auction mechanisms are discussed.
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
Bogg, P.: http://www-staff.it.uts.edu.au/plbogg/negotiation/demos/maxent/
Castro-Schez, J., Jennings, N., Luo, X., Shadbolt, N.: Acquiring domain knowledge for negotiating agents: a case study. Int. J. of Human-Computer Studies (to appear, 2004)
Debenham, J.: Bargaining with information. In: Proceedings Third International Conference on Autonomous Agents and Multi Agent Systems AAMAS 2004 (July 2004)
Halpern, J.: Reasoning about Uncertainty. MIT Press, Cambridge (2003)
Jaeger, M.: Representation independence of nonmonotonic inference relations. In: Proceedings of KR 1996, pp. 461–472. Morgan Kaufmann, San Francisco (1996)
Jaynes, E.: Information theory and statistical mechanics: Part i. Physical Review 106, 620–630 (1957)
Klemperer, P.: The Economic Theory of Auctions: Vols I and II. Edward Elgar (2000)
MacKay, D.: Information Theory, Inference and Learning Algorithms. Cambridge University Press, Cambridge (2003)
Myerson, R., Satterthwaite, M.: Efficient mechanisms for bilateral trading. Journal of Economic Theory 29, 1–21 (1983)
Paris, J.: Common sense and maximum entropy. Synthese 117(1), 75–93 (1999)
Pietra, S.D., Pietra, V.D., Lafferty, J.: Inducing features of random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(2), 380–393 (1997)
Ramchurn, S., Jennings, N., Sierra, C., Godo, L.: A computational trust model for multi-agent interactions based on confidence and reputation. In: Proceedings 5th Int. Workshop on Deception, Fraud and Trust in Agent Societies (2003)
Sandholm, T., Vulkan, N.: Bargaining with deadlines. In: Proceedings of the National Conference on Artificial Intelligence (AAAI) (1999)
Varian, H.: Mechanism design for computerized agents. In: Proceedings Usenix Workshop on Electronic Commerce, pp. 13–21 (July 1995)
Wolfstetter, E.: Topics in Microeconomics. Cambridge UP (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Debenham, J. (2006). Auctions and Bidding with Information. In: Faratin, P., Rodríguez-Aguilar, J.A. (eds) Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems. AMEC 2004. Lecture Notes in Computer Science(), vol 3435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575726_9
Download citation
DOI: https://doi.org/10.1007/11575726_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29737-6
Online ISBN: 978-3-540-33166-7
eBook Packages: Computer ScienceComputer Science (R0)