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An Ironing-Based Approach to Adaptive Online Mechanism Design in Single-Valued Domains

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2007

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http://portal.acm.org/citation.cfm?id=1619645.1619661

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American Association for Artificial Intelligence
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Parkes, David C. and Quang Duong. 2007. An ironing-based approach to adaptive online mechanism design in single-valued domains. In Proceedings of the Twenty-second AAAI Conference on Artificial Intelligence: July 22-26, 2007, Vancouver, British Columbia, Canada, ed. American Association for Artificial Intelligence, 94-101. Menlo Park, Calif.: AAAI Press.

Abstract

Online mechanism design considers the problem of sequential decision making in a multi-agent system with self-interested agents. The agent population is dynamic and each agent has private information about its value for a sequence of decisions. We introduce a method ("ironing") to transform an algorithm for online stochastic optimization into one that is incentive-compatible. Ironing achieves this by canceling decisions that violate a form of monotonicity. The approach is applied to the CONSENSUS algorithm and experimental results in a resource allocation domain show that not many decisions need to be canceled and that the overhead of ironing is manageable.

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http://www.eecs.harvard.edu/econcs/pubs/aaai07.pdf

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http://nrs.harvard.edu/urn-3:HUL.InstRepos:4039777

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