An implementation of genetic algorithms for rule based machine learning

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "S. Sette and L. Boullart",
  title =        "An implementation of genetic algorithms for rule based
                 machine learning",
  journal =      "Engineering Applications of Artificial Intelligence",
  year =         "2000",
  volume =       "13",
  pages =        "381--390",
  number =       "4",
  keywords =     "genetic algorithms, genetic programming, Genetic based
                 machine learning, Learning classifier systems, Fuzzy
                 efficiency based classifier systems, Textiles,
                 Production process",
  ISSN =         "0952-1976",
  owner =        "wlangdon",
  URL =          "",
  DOI =          "doi:10.1016/S0952-1976(00)00020-8",
  abstract =     "Genetic algorithms have given rise to two new fields
                 of research where (global) optimisation is of crucial
                 importance: 'Genetic Programming' and 'Genetic based
                 Machine Learning' (GBML). An overview of one of the
                 first GBML implementations by Holland, also known as
                 the Learning Classifier Systems (LCS) will be given.
                 After describing and solving a well-known basic
                 (educational) problem a more complex application of
                 GBML is presented. The goal of this application is the
                 automatic development of a rule set for an industrial
                 production process. To this end, the case study on
                 generating a rule set for predicting the spinnability
                 in the fibre-to-yarn production process will be
                 presented. A largely modified LCS, called Fuzzy
                 Efficiency based Classifier System (FECS), originally
                 designed by one of the authors, is used to solve this
                 problem successfully.",

Genetic Programming entries for Stefan Sette Luc Boullart