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Time Management for Monte-Carlo Tree Search in Go

  • Hendrik Baier
  • Mark H. M. Winands
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7168)

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.

Keywords

Time Management Search Time Time Allocation Dynamic Strategy Good Move 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hendrik Baier
    • 1
  • Mark H. M. Winands
    • 1
  1. 1.Games and AI Group, Department of Knowledge EngineeringMaastricht UniversityMaastrichtThe Netherlands

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