Deriving multi-agent coordination through filtering strategies

Authors:
Eithan Ephrati;Martha E. Pollack;Sigalit Ur
Affiliations:
Department of Computer Science, University of Pittsburgh;Department of Computer Science, University of Pittsburgh and Intelligent Systems Program;Intelligent Systems Program, University of Pittsburgh
Venue:
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Year:
1995

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Abstract

We examine an approach to multi-agent coordination that builds on earlier work on enabling single agents to control their reasoning in dynamic environments. Specifically, we study a generalization of the filtering strategy. Where single-agent filtering means tending to bypass options that are incompatible with an agent's own goals, multi-agent filtering means tending to bypass options that are incompatible with other agents' known or presumed goals. We examine several versions of multi-agent filtering, which range from purely implicit to minimally explicit, and discuss the trade-offs among these. We also describe a series of experiments that demonstrate initial results about the feasibility of using multi-agent filtering to achieve coordination without explicit negotiation.