Comparing learning classifier systems and Genetic Programming: a case study

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "S. Sette and B. Wyns and L. Boullart",
  title =        "Comparing learning classifier systems and Genetic
                 Programming: a case study",
  journal =      "Engineering Applications of Artificial Intelligence",
  year =         "2004",
  volume =       "17",
  pages =        "199--204",
  number =       "2",
  abstract =     "Genetic Algorithms has given rise to two new fields of
                 research where (global) optimisation is of crucial
                 importance: 'genetic based machine learning' (GBML) and
                 'genetic programming' (GP). An advanced implementation
                 of GBML (Fuzzy Efficiency based Classifier System,
                 FECS, developed by the authors) and GP (as defined by
                 Koza) are both applied to the case study 'fibre-to-yarn
                 production process'. Results for both systems are
                 presented and compared. Finally, the GP generated
                 equations are transformed into rule-sets similar to
                 those obtained from FECS.",
  owner =        "wlangdon",
  URL =          "",
  keywords =     "genetic algorithms, genetic programming, Textile
                 production process, Learning classifier systems,
                 Rule-based machine learning",
  DOI =          "doi:10.1016/j.engappai.2004.02.006",

Genetic Programming entries for Stefan Sette Bart Wyns Luc Boullart