Multi-agent based solutions to problems, whether they are software agents or physical robots, are attractive because they are robust and scalable. Fundamental aspects of designing multi-agent systems involve modeling the intelligence of the agents and modeling their interactions. The intelligences of agents modeled here are encoded in Bayesian representations of their world. The agents interact only by observing others and moving in such a way so as to probabilistically maximize their internalized goal or utility. Using this multi-agent framework, a three agent herding is explored.

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Copyright 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ISBN: 0-7803-7952-7Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Conference Proceeding

Department, Program, or Center

Microelectronic Engineering (KGCOE)


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