Discovery of Neural Network Learning Rules Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Amr M. Radi and Riccardo Poli",
  title =        "Discovery of Neural Network Learning Rules Using
                 Genetic Programming",
  institution =  "University of Birmingham, School of Computer Science",
  number =       "CSRP-97-21",
  month =        sep,
  year =         "1997",
  file =         "/1997/",
  URL =          "",
  ftpaddress =   "",
  reportfilename = "pub/tech-reports/1997/",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "The development of the backpropagation learning rule
                 has been a land mark in neural networks. It provides a
                 computational method for training multi layer networks.
                 Unfortunately, backpropagation suffers from several
                 problems. a new technique based upon Genetic
                 Programming (GP) is proposed to overcome some of these
                 problems. We have used GP to discover new supervised
                 learning algorithms. A set of such learning algorithms
                 has been compared with the Standard BackPropagation
                 (SBP) learning algorithm on different problems and has
                 been shown to provide better performances. This study
                 indicates that there exist many supervised learning
                 algorithms better than, but similar to, SBP and that GP
                 can be used to discover them.",

Genetic Programming entries for Amr Mohamed Mahmoud Khairat Radi Riccardo Poli