Evolution of the Topology and the Weights of Neural Networks using Genetic Programming with a Dual Representation

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@TechReport{Pujol:1997:etwNNGP,
  author =       "Joao Carlos Figueira Pujol and Riccardo Poli",
  title =        "Evolution of the Topology and the Weights of Neural
                 Networks using Genetic Programming with a Dual
                 Representation",
  institution =  "University of Birmingham, School of Computer Science",
  number =       "CSRP-97-7",
  month =        feb,
  year =         "1997",
  email =        "R.Poli@cs.bham.ac.uk",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1997/CSRP-97-07.ps.gz",
  abstract =     "Genetic programming is a methodology for program
                 development, consisting of a special form of genetic
                 algorithm capable of handling parse trees representing
                 programs, that has been successfully applied to a
                 variety of problems. In this paper a new approach to
                 the construction of neural networks based on genetic
                 programming is presented. A linear chromosome is
                 combined to a graph representation of the network and
                 new operators are introduced, which allow the evolution
                 of the architecture and the weights simultaneously
                 without the need of local weight optimization. This
                 paper describes the approach, the operators and reports
                 results of the application of the model to several
                 binary classification problems.",
  notes =        "See also \cite{Pujol:1998:etwNNGP}",
}

Genetic Programming entries for Joao Carlos Figueira Pujol Riccardo Poli

Citations