A biological decision-theoretic intelligent agent solution to aherding problem in the context of distributed multi-agent systems

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Title: A biological decision-theoretic intelligent agent solution to aherding problem in the context of distributed multi-agent systems
Author: Sahin, Ferat; Bay, John
Abstract: 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.
Description: 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. 
Record URI: http://hdl.handle.net/1850/8947
Date: 2000-10

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