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.
Edmund H. Durfee, Daniel L. Kiskis, and William P. Birmingham.
"The Agent Architecture of the University of Michigan Digital Library."
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(Special Issue on Intelligent Agents), 144(1):61-71, February
1997.
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.
Sunju Park, Edmund H. Durfee, and William P. Birmingham. "Advantages of Strategic Thinking in Multiagent Contracts (A Mechanism and Analysis)."
In Proceedings of the Second International Conference on Multi-Agent
Systems (ICMAS96), pages 259-266, December 1996.
José M. Vidal and Edmund H. Durfee. "Using Recursive Agent Models Effectively,"
in M. Wooldridge, J. Muller, and M. Tambe (eds.) Intelligent
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José M. Vidal and Edmund H. Durfee. "Recursive Agent Modeling Using Limited Rationality."
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Economic forces can be used for efficient allocation of information resources, and given sufficient time and stability information economies can settle into equilibria. However, our view of these economies is as open, constantly evolving systems. It can therefore be crucial for an agent that is part of such an economy to maintain and use models of the evolving provision and consumption properties of the agents around it, so as to make the most effective decisions possible. Our work involves acquiring models of agents in such an economy (including models of their models, and so on), and using these to envision possible patterns of buying and selling, such that an agent can maximize its expected payoff in the information economy.