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Learning from Perfection

A Data Mining Approach to Evaluation Function Learning in Awari

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Computers and Games (CG 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2063))

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Abstract

Automatic tuning of evaluation function parameters for game playing programs, and automatic discovery of the very features that these parameters refer to, are challenging but potentially very powerful tools. While some advances have been made in parameter tuning, the field of feature discovery is still in its infancy. The game ofAwari offers the possibility to achieve both goals. This paper describes the efforts to design an evaluation function without any human expertise as part of the Awari playing program Bambam, as being developed by the Awari team1 at the University of Alberta.

See http://www.cs.ualberta.ca/~awari.

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References

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© 2001 Springer-Verlag Berlin Heidelberg

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van Rijswijck, J. (2001). Learning from Perfection. In: Marsland, T., Frank, I. (eds) Computers and Games. CG 2000. Lecture Notes in Computer Science, vol 2063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45579-5_8

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  • DOI: https://doi.org/10.1007/3-540-45579-5_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43080-3

  • Online ISBN: 978-3-540-45579-0

  • eBook Packages: Springer Book Archive

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