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European Conference on Genetic Programming

EuroGP 2005: Genetic Programming pp 120–131Cite as

GP-EndChess: Using Genetic Programming to Evolve Chess Endgame Players

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3447))

Abstract

We apply genetic programming to the evolution of strategies for playing chess endgames. Our evolved programs are able to draw or win against an expert human-based strategy, and draw against CRAFTY—a world-class chess program, which finished second in the 2004 Computer Chess Championship.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Ben-Gurion University, Israel

    Ami Hauptman & Moshe Sipper

Authors
  1. Ami Hauptman
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  2. Moshe Sipper
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Editor information

Editors and Affiliations

  1. No Affiliation,  

    Maarten Keijzer

  2. Dipartimento di Tecnologie dell’Informazione, Università di Milano Crema,  

    Andrea Tettamanzi

  3. Université Louis Pasteur, LSIIT, FDBT, Pôle API, F-67400, Illkirch, France

    Pierre Collet

  4. National e-Science Centre, University of Edinburgh, United Kingdom

    Jano van Hemert

  5. Institut des Systèmes d’Information (ISI), Université de Lausanne, Hautes Etudes Commerciales (HEC),  

    Marco Tomassini

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© 2005 Springer-Verlag Berlin Heidelberg

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Hauptman, A., Sipper, M. (2005). GP-EndChess: Using Genetic Programming to Evolve Chess Endgame Players. In: Keijzer, M., Tettamanzi, A., Collet, P., van Hemert, J., Tomassini, M. (eds) Genetic Programming. EuroGP 2005. Lecture Notes in Computer Science, vol 3447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31989-4_11

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  • DOI: https://doi.org/10.1007/978-3-540-31989-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25436-2

  • Online ISBN: 978-3-540-31989-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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