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Creating an Upper-Confidence-Tree Program for Havannah

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Advances in Computer Games (ACG 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6048))

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Abstract

Monte-Carlo Tree Search and Upper Confidence Bounds provided huge improvements in computer-Go. In this paper, we test the generality of the approach by experimenting on the game, Havannah, which is known for being especially difficult for computers. We show that the same results hold, with slight differences related to the absence of clearly known patterns for the game of Havannah, in spite of the fact that Havannah is more related to connection games like Hex than to territory games like Go.

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Author information

Authors and Affiliations

  1. TAO (Inria), LRI, UMR 8623(CNRS - Univ. Paris-Sud), bat 490 Univ. Paris-Sud, 91405, Orsay, France

    Fabien Teytaud & Olivier Teytaud

Authors
  1. Fabien Teytaud
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  2. Olivier Teytaud
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Editor information

Editors and Affiliations

  1. Games and AI Group, MICC, Faculty of Humanities and Sciences, Universiteit Maastricht, Maastricht, The Netherlands

    H. Jaap van den Herik

  2. Institute for Knowledge and Agent Technology, Universiteit Maastricht,  

    Pieter Spronck

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Teytaud, F., Teytaud, O. (2010). Creating an Upper-Confidence-Tree Program for Havannah. In: van den Herik, H.J., Spronck, P. (eds) Advances in Computer Games. ACG 2009. Lecture Notes in Computer Science, vol 6048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12993-3_7

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  • DOI: https://doi.org/10.1007/978-3-642-12993-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12992-6

  • Online ISBN: 978-3-642-12993-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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