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The Impact of Nested Agent Models in an Information Economy

José M. Vidal and Edmund H. Durfee
Artificial Intelligence Laboratory, University of Michigan
1101 Beal Avenue, Ann Arbor, MI 48109-2110

August 21, 1996


We present our approach to the problem of how an agent, within an economic Multi-Agent System, can determine when it should behave strategically (i.e. model the other agents), and when it should act as a simple price-taker. We provide a framework for the incremental implementation of modeling capabilities in agents. These agents were implemented and different populations simulated in order to learn more about their behavior and the merits of using agent models. Our results show, among other lessons, how savvy buyers can avoid being ``cheated'' by sellers, how price volatility can be used to quantitatively predict the benefits of deeper models, and how specific types of agent populations influence system behavior.

Topic Areas: Agent Modeling/Learning, Economic Societies of Agents.

Jose M. Vidal
Wed Aug 21 07:12:37 EDT 1996