Evolving Modular Neural Networks Using Rule-Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Bret Talko and Linda Stern and Les Kitchen",
  title =        "Evolving Modular Neural Networks Using Rule-Based
                 Genetic Programming",
  booktitle =    "12th Australian Joint Conference on Artificial
  year =         "1999",
  editor =       "Norman Foo",
  volume =       "1747",
  series =       "LNCS",
  pages =        "482--483",
  address =      "Sydney, Australia",
  publisher_address = "Berlin",
  month =        "6-10 " # dec,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-66822-5",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/12028/http:zSzzSzwww.cs.mu.oz.auzSz~talkozSzposterai99.pdf/evolving-modular-neural-networks.pdf",
  URL =          "http://citeseer.ist.psu.edu/284438.html",
  URL =          "http://fluid.mech.okayama-u.ac.jp/brett/evolving-modular-neural-networks.ps
  URL =          "http://www.springer.com/computer/ai/book/978-3-540-66822-0",
  size =         "2 pages",
  abstract =     "his paper describes a new approach for evolving
                 recurrent neural networks using Genetic Programming. A
                 system has been developed to train weightless neural
                 networks using construction rules. The network
                 construction rules are evolved by the Genetic
                 Programming system which build the solution neural
                 networks. The use of rules allows networks to be
                 constructed modularly. Experimentation with
                 decomposable Boolean functions has revealed that the
                 performance of the system is superior to a...",
  notes =        "http://www.cse.unsw.edu.au/~ai99/ masters thesis",

Genetic Programming entries for Bret Talko Linda Stern Les Kitchen