Evolving multi-agents using a self-organizing genetic algorithm

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Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the ways to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover rules that govern emergent cooperative behavior. A self-organizing genetic algorithm was applied to automating the discovery of rules for multi-agents playing soccer. A model consisting of movable agents in a cellular space is introduced. Simulation results indicate that, given the complexity of the problem an evolutionary approach to finding the appropriate rules seems to be promising. The implications of the results are discussed. (C) Elsevier Science Inc., 1997.
Publisher
ELSEVIER SCIENCE INC
Issue Date
1997-12
Language
English
Article Type
Article
Citation

APPLIED MATHEMATICS AND COMPUTATION, v.88, no.2-3, pp.293 - 303

ISSN
0096-3003
URI
http://hdl.handle.net/10203/8268
Appears in Collection
EE-Journal Papers(저널논문)
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