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A Study of UCT and Its Enhancements in an Artificial Game

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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, especially the UCT algorithm and its enhancements, have become extremely popular. Because of the importance of this family of algorithms, a deeper understanding of when and how the different enhancements work is desirable. To avoid the hard to analyze intricacies of tournament-level programs in complex games, this work focuses on a simple abstract game, which is designed to be ideal for history-based heuristics such as RAVE. Experiments show the influence of game complexity and of enhancements on the performance of Monte-Carlo Tree Search.

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Author information

Authors and Affiliations

  1. Department of Computing Science, University of Alberta, Edmonton, Canada, T6G 2E8

    David Tom & Martin Müller

Authors
  1. David Tom
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  2. Martin Müller
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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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Tom, D., Müller, M. (2010). A Study of UCT and Its Enhancements in an Artificial Game. 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_6

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  • DOI: https://doi.org/10.1007/978-3-642-12993-3_6

  • 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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