DC Field | Value | Language |
---|---|---|
dc.contributor.author | Il-Kwon Jeong | ko |
dc.contributor.author | Ju-Jang Lee | ko |
dc.date.accessioned | 2008-12-22T02:34:07Z | - |
dc.date.available | 2008-12-22T02:34:07Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1999 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF CONTROL, AUTOMATION, AND SYSTEMS | - |
dc.identifier.issn | 1598-6446 | - |
dc.identifier.uri | http://hdl.handle.net/10203/8159 | - |
dc.description.abstract | It is an interesting area in the field of artifical intelligence to find an analytic model of cooperative structure for multiagent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way 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 a fuzzy logic controller with rules that govern emergent agents solving a pursuit problem in a continuous world. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to find the fuzzy logic controller seems to be promising. | - |
dc.language | Korean | - |
dc.language.iso | en | en |
dc.publisher | 제어·로봇·시스템학회/대한전기학회 | - |
dc.title | Evoluationary Design of a Fuzzy Logic Controller For Multi-Agent Robotic Systems | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF CONTROL, AUTOMATION, AND SYSTEMS | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Ju-Jang Lee | - |
dc.contributor.nonIdAuthor | Il-Kwon Jeong | - |
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