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:
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reproduction of the XOR function which validates the method used
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generation of an evaluation function
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Autonès, M., Beck, A., Camacho, P., Lassabe, N., Luga, H., Scharffe, F. (2004). Evaluation of Chess Position by Modular Neural Network Generated by Genetic Algorithm. In: Keijzer, M., O’Reilly, UM., Lucas, S., Costa, E., Soule, T. (eds) Genetic Programming. EuroGP 2004. Lecture Notes in Computer Science, vol 3003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24650-3_1
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DOI: https://doi.org/10.1007/978-3-540-24650-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21346-8
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