Dual network representation applied to the evolution of neural controllers (original) (raw)

Abstract

This paper presents a new approach to the evolution of neural networks. A linear chromosome combined with a grid-based representation of the network and a new crossover operator allow the evolution of the architecture and the weights simultaneously. There is no need for a separate weight optimization procedure and networks with more than one type of activation function can be evolved. This paper describes the representation, the crossover operator, and reports on results of the application of the method to evolve a neural controller for the pole-balancing problem.

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Authors and Affiliations

  1. School of Computer Science, The University of Birmingham, B15 2TT, Birmingham, UK
    João Carlos Figueira Pujol & Riccardo Poli

Authors

  1. João Carlos Figueira Pujol
  2. Riccardo Poli

Editor information

V. W. Porto N. Saravanan D. Waagen A. E. Eiben

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© 1998 Springer-Verlag Berlin Heidelberg

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Pujol, J.C.F., Poli, R. (1998). Dual network representation applied to the evolution of neural controllers. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040815

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