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

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 incentivecompatible. 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.

• Type: Conference
• Year: 2007
• Where: AAAI
• Authors: David C. Parkes, Quang Duong
• Keywords: AAAI 2007, Intelligent Agents, Ironing, Online Mechanism Design, Sequential Decision Making