A novel genetic cooperative-competitive fuzzy rule based learning method using genetic programming for high dimensional problems

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Berlanga:2008:GEFS,

• author = "Francisco Jose Berlanga and Maria Jose {del Jesus} and Francisco Herrera",
• title = "A novel genetic cooperative-competitive fuzzy rule based learning method using genetic programming for high dimensional problems",
• booktitle = "3rd International Workshop on Genetic and Evolving Fuzzy Systems, GEFS 2008",
• year = "2008",
• month = "4-7 " # mar,
• address = "Witten-Boommerholz, Germany",
• pages = "101--106",
• keywords = "genetic algorithms, genetic programming, genetic cooperative-competitive fuzzy rule based learning method, high dimensional classification problems, high dimensional problems, token competition mechanism, fuzzy set theory, knowledge based systems, learning (artificial intelligence)",
• DOI = "doi:10.1109/GEFS.2008.4484575",
• abstract = "In this contribution, we present GP-COACH, a novel GFS based on the cooperative-competitive learning approach, that uses genetic programming to code fuzzy rules with a different number of variables, for getting compact and accurate rule bases for high dimensional problems. GP-COACH learns disjunctive normal form rules (generated by means of a context-free grammar) and uses a token competition mechanism to maintain the diversity of the population. It makes the rules compete and cooperate among themselves, giving out a compact set of fuzzy rules that presents a good performance. The good results obtained in an experimental study involving several high dimensional classification problems support our proposal.",
• notes = "Also known as \cite{4484575}",

}

Genetic Programming entries for Francisco Jose Berlanga Maria Jose del Jesus Francisco Herrera

Citations