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International Conference on Innovative Techniques and Applications of Artificial Intelligence

SGAI 2012: Research and Development in Intelligent Systems XXIX pp 93–106Cite as

Using Chunks to Categorise Chess Positions

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Abstract

Expert computer performances in domains such as chess are achieved by techniques different from those which can be used by a human expert. The match between Gary Kasparov and Deep Blue shows that human expertise is able to balance an eight-magnitude difference in computational speed. Theories of human expertise, in particular the chunking and template theories, provide detailed computational models of human long-term memory, how it is acquired and retrieved. We extend an implementation of the template theory, CHREST, to support the learning and retrieval of categorisations of chess positions. Our extended model provides equivalent performance to a support-vector machine in categorising chess positions by opening, and reveals how learning for retrieval relates to learning for content.

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Author information

Authors and Affiliations

  1. School of Computer Science, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK

    Peter C. R. Lane

  2. School of Social Sciences, Brunel University, Uxbridge, UX3 8BH, UK

    Fernand Gobet

Authors
  1. Peter C. R. Lane
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  2. Fernand Gobet
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Correspondence to Peter C. R. Lane .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Whitepost Lane The Lilacs, Portsmouth, PO1 3AH, Hampshire, United Kingdom

    Max Bramer

  2. School of Computing, Engineering & Mathe, University of Brighton, Lewes Road, Brighton, BN2 4GJ, West Sussex, United Kingdom

    Miltos Petridis

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© 2012 Springer-Verlag London

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Lane, P.C.R., Gobet, F. (2012). Using Chunks to Categorise Chess Positions. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXIX. SGAI 2012. Springer, London. https://doi.org/10.1007/978-1-4471-4739-8_7

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  • DOI: https://doi.org/10.1007/978-1-4471-4739-8_7

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4738-1

  • Online ISBN: 978-1-4471-4739-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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