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Time Management for Monte-Carlo Tree Search in Go

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Advances in Computer Games (ACG 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7168))

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Abstract

The dominant approach for programs playing the game of Go is nowadays Monte-Carlo Tree Search (MCTS). While MCTS allows for fine-grained time control, little has been published on time management for MCTS programs under tournament conditions. This paper investigates the effects that various time-management strategies have on the playing strength in Go. We consider strategies taken from the literature as well as newly proposed and improved ones. We investigate both semi-dynamic strategies that decide about time allocation for each search before it is started, and dynamic strategies that influence the duration of each move search while it is already running. In our experiments, two domain-independent enhanced strategies, EARLY-C and CLOSE-N, are tested; each of them provides a significant improvement over the state of the art.

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Author information

Authors and Affiliations

  1. Games and AI Group, Department of Knowledge Engineering, Maastricht University, Maastricht, The Netherlands

    Hendrik Baier & Mark H. M. Winands

Authors
  1. Hendrik Baier
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  2. Mark H. M. Winands
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Editor information

Editors and Affiliations

  1. Tilburg Institute of Cognition and Communication, Tilburg University, Warandelaan 2, 5037 AB, Tilburg, The Netherlands

    H. Jaap van den Herik  & Aske Plaat  & 

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Baier, H., Winands, M.H.M. (2012). Time Management for Monte-Carlo Tree Search in Go. In: van den Herik, H.J., Plaat, A. (eds) Advances in Computer Games. ACG 2011. Lecture Notes in Computer Science, vol 7168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31866-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-31866-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31865-8

  • Online ISBN: 978-3-642-31866-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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