Proposes a biological decision-theoretic intelligent agent model to solve a herding problem. The proposed intelligent agent model is designed by combining Bayesian networks and influence diagrams. In our agent design, we used Y. Shoham's (1993) agent-oriented programming paradigm that defines an intelligent agent by its belief, preference and capabilities. Intelligent agent software is written to realize the proposed intelligent agent model. The same software is then used to simulate the herding problem with one sheep and one dog. Simulation results show that the proposed intelligent agent is successful in establishing a goal (herding) and learning other agents' behaviors.

Date of creation, presentation, or exhibit



2000 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: 0-7803-6583-6Note: 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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