José M. Vidal and Edmund H. Durfee. "Learning Nested Agent Models in an Information Economy." Journal of Experimental and Theoretical Artificial Intelligence (special issue on learning in distributed artificial intelligence systems). To appear.
José M. Vidal and Edmund H. Durfee. "The Impact of Nested Agent Models in an Information Economy." In Proceedings of the Second International Conference on Multi-Agent Systems (ICMAS96), pages 377-384, December 1996.
Piotr J. Gmytrasiewicz and Edmund H. Durfee. "A Rigorous, Operational Formalization of Recursive Modeling." In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS), pages 125-132, June 1995.
José M. Vidal and Edmund H. Durfee. "Recursive Agent Modeling Using Limited Rationality." In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS), pages 376-383, June 1995.
Piotr J. Gmytrasiewicz and Edmund H. Durfee. Toward a Theory of Honesty and Trust Among Communicating Autonomous Agents. Group Decision and Negotiation 2:237-258 (Special issue on Distributed Artificial Intelligence), 1993.
Piotr J. Gmytrasiewicz and Edmund H. Durfee. Elements of a Utilitarian Theory of Knowledge and Action. In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, pages 396-402, August 1993.
Edmund H. Durfee, Jaeho Lee, and Piotr J. Gmytrasiewicz. Overeager Reciprocal Rationality and Mixed Strategy Equilibria. In Proceedings of the Eleventh National Conference on Artificial Intelligence, pages 225-230, July 1993.
Piotr J. Gmytrasiewicz and Edmund H. Durfee. A Logic of Knowledge and Belief for Recursive Modeling: Preliminary report. In Proceedings of the Tenth National Conference on Artificial Intelligence, pages 628-634, July 1992.
Piotr J. Gmytrasiewicz, Edmund H. Durfee, and David K. Wehe. A Decision-Theoretic Approach to Coordinating Multiagent Interactions. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, pages 62-68, August 1991.
Piotr J. Gmytrasiewicz, Edmund H. Durfee, and David K. Wehe. The Utility of Communication in Coordinating Intelligent Agents. In Proceedings of the Ninth National Conference on Artificial Intelligence, pages 166-172, July 1991.
Piotr J. Gmytrasiewicz and Edmund H.Durfee. Decision-Theoretic Recursive Modeling and the Coordinated Attack Problem. In Proceedings of the First International Conference on AI Planning Systems, June 1992.
Edmund H. Durfee, Piotr J. Gmytrasiewicz, and Jeffrey S. Rosenschein. The Utility of Embedded Communications: Toward the Emergence of Protocols. In Proceedings of the Thirteenth International Distributed Artificial Intelligence Workshop, pages 85-93, July 1994.
Jose Vidal and Edmund H. Durfee. RMM's Solution Concept and the Equilibrium Point Solution In Proceedings of the Thirteenth International Distributed Artificial Intelligence Workshop, pages 363-377, July 1994.
Piotr J. Gmytrasiewicz and Edmund H. Durfee. Reasoning about Other Agents: Philosophy, Theory, and Implementation. In Proceedings of The Twelfth International Workshop on Distributed Artificial Intelligence , May 1993. Also appeared in the preproceedings of the workshop on Modeling Autonomous Agents in Multiagent Worlds, August 1993.
To decide what to do in a multiagent world, an agent should model what others might simultaneously be deciding to do, but that in turn requires modeling what those others might think that others are deciding to do, and so on. The Recursive Modeling Method (RMM) provides representations and algorithms for developing these nested models of beliefs and using them to make rational choices of action. RMM has evolved into a suite of techniques that allow a wide variety of reasoning behavior, including reasoning about communicative and computative actions as well as physical actions.
However, because these nested models can involve many branches and extend to deep levels of recursion, making decisions in time-constrained multiagent worlds requires methods for inexpensive approximation and for metareasoning to balance the quality of decisions with the costs of making them. In this abstract, we summarize our work along these lines.