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

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