The Temporal Fuzzy Classifier System and its Application to Distributed Control in a Homogeneous Multi-Agent ecology   [CS] [DC]

by

Carse, B., Fogarty, T., C. and Munro, A.

Literature search on Evolutionary ComputationBBase ©1999-2013, Rasmus K. Ursem
     Home · Search · Adv. search · Authors · Login · Add entries   Webmaster
Note to authors: Please submit your bibliography and contact information - online papers are more frequently cited.

Info: Proceedings of the First International Conference on Evolutionary Algorithms and their Application EVCA'96 (Conference proceedings), 1996, p. 76-86
Keywords:LCS
Abstract:
A fuzzy classifier system [CS] is described which explicitly represents time in the classifier syntax by augmenting individual classifiers with temporal tags. This feature allows the learning algorithm - in this case the genetic algorithm [GA] - to explore and exploit temporal features of the environment in which the classifier system [CS] might be expected to operate. The proposed temporal fuzzy classifier system [CS] is applied to a multi-agent distributed control task [DC] - adaptive distributed rooting in packet-switched communications networks.
Internet search:Search Google
Search Google Scholar
Search Citeseer using Google
Search Google for PDF
Search Google Scholar for PDF
Search Citeseer for PDF using Google

Review item:

Mark as doublet (will be reviewed)

Print entry




BibTex:
@InProceedings{Carse1996c,
  author =       "Brian Carse and Terence C. Fogarty and A. Munro",
  title =        "{The Temporal Fuzzy Classifier System and its
                 Application to Distributed Control in a Homogeneous
                 Multi-Agent ecology}",
  pages =        "76--86",
  booktitle =    "{Proceedings of the First International Conference on
                 Evolutionary Algorithms and their Application
                 EVCA'96}",
  year =         "1996",
  editor =       "E. G. Goodman and V. L. Uskov and W. F. Punch",
  organization = "The Presidium of the Russian Academy of Sciences",
  address =      "Moscow",
  keywords =     "LCS",
  abstract =     "A fuzzy classifier system is described which
                 explicitly represents time in the classifier syntax by
                 augmenting individual classifiers with temporal tags.
                 This feature allows the learning algorithm - in this
                 case the genetic algorithm - to explore and exploit
                 temporal features of the environment in which the
                 classifier system might be expected to operate. The
                 proposed temporal fuzzy classifier system is applied to
                 a multi-agent distributed control task - adaptive
                 distributed rooting in packet-switched communications
                 networks.",
}