dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorNakamiti, G.
dc.creatorFreitas, R.
dc.creatorPrado, J.
dc.creatorGomide, F.
dc.date2014-05-27T11:17:58Z
dc.date2016-10-25T18:13:22Z
dc.date2014-05-27T11:17:58Z
dc.date2016-10-25T18:13:22Z
dc.date1994-12-01
dc.date.accessioned2017-04-06T00:45:32Z
dc.date.available2017-04-06T00:45:32Z
dc.identifierIEEE International Conference on Fuzzy Systems, v. 1, p. 462-467.
dc.identifierhttp://hdl.handle.net/11449/64523
dc.identifierhttp://acervodigital.unesp.br/handle/11449/64523
dc.identifier10.1109/FUZZY.1994.343741
dc.identifierWOS:A1994BC17S00083
dc.identifier2-s2.0-0028730128
dc.identifierhttp://dx.doi.org/10.1109/FUZZY.1994.343741
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/886345
dc.descriptionIn this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.
dc.languageeng
dc.relationIEEE International Conference on Fuzzy Systems
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial intelligence
dc.subjectComputer systems
dc.subjectDistributed parameter control systems
dc.subjectFormal logic
dc.subjectKnowledge representation
dc.subjectTraffic control
dc.subjectTraffic signals
dc.subjectFuzzy distributed artificial intelligence systems
dc.subjectFuzzy systems
dc.subjectTraffic light control
dc.subjectFuzzy sets
dc.titleFuzzy distributed artificial intelligence systems
dc.typeOtro


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