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Evaluation of Chess Position by Modular Neural Network Generated by Genetic Algorithm

  • Mathieu Autonès
  • Ariel Beck
  • Philippe Camacho
  • Nicolas Lassabe
  • Hervé Luga
  • François Scharffe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3003)

Abstract

In this article we present our chess engine Tempo. One of the major difficulties for this type of program lies in the function for evaluating game positions. This function is composed of a large number of parameters which have to be determined and then adjusted. We propose an alternative which consists in replacing this function by an artificial neuron network (ANN). Without topological knowledge of this complex network, we use the evolutionist methods for its inception, thus enabling us to obtain, among other things, a modular network. Finally, we present our results:
  • reproduction of the XOR function which validates the method used

  • generation of an evaluation function

Keywords

Genetic Algorithm Evaluation Function Modular Network Modular Neural Network Chess Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Mathieu Autonès
    • 1
  • Ariel Beck
    • 1
  • Philippe Camacho
    • 1
  • Nicolas Lassabe
    • 1
  • Hervé Luga
    • 1
  • François Scharffe
    • 1
  1. 1.Institut de Recherche en Informatique de ToulouseUniversité Paul SabatierToulouse cedexFrance

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