Discovering efficient learning rules for feedforward neural networks using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{radi:2003:RAIPA,
  author =       "Amr Radi and Riccardo Poli",
  title =        "Discovering efficient learning rules for feedforward
                 neural networks using genetic programming",
  booktitle =    "Recent advances in intelligent paradigms and
                 applications",
  year =         "2003",
  ISBN =         "3-7908-1538-1",
  pages =        "133--159",
  publisher =    "Physica-Verlag GmbH",
  address =      "Heidelberg, Germany, Germany",
  editor =       "Ajith Abraham and Lakhmi Jain and Janusz Kacprzyk",
  chapter =      "7",
  keywords =     "genetic algorithms, genetic programming, ANN",
  URL =          "http://www.springer.com/computer/ai/book/978-3-7908-1538-2",
  abstract =     "The Standard BackPropagation (SBP) algorithm is the
                 most widely known and used learning method for training
                 neural networks. Unfortunately, SBP suffers from
                 several problems such as sensitivity to the initial
                 conditions and very slow convergence. Here we describe
                 how we used Genetic Programming, a search algorithm
                 inspired by Darwinian evolution, to discover new
                 supervised learning algorithms for neural networks
                 which can overcome some of these problems. Comparing
                 our new algorithms with SBP on different problems we
                 show that these are faster, are more stable and have
                 greater feature extracting capabilities.",
  notes =        "See also \cite{radi:2002:CSM360}",
}

Genetic Programming entries for Amr Mohamed Mahmoud Khairat Radi Riccardo Poli

Citations