Single-Player Monte-Carlo Tree Search

Maarten P. D. Schadd*, Mark H. M. Winands, H. Jaap van den Herik, Guillaume M. J. -B. Chaslot, Jos W. H. M. Uiterwijk

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

Classical methods such as a* and ida* are a popular and successful choice for one-player games. However, they fail without an accurate admissible evaluation function. In this paper we investigate whether monte-carlo tree search (mcts) is an interesting alternative for one-player games where a* and ida* methods do not perform well. Therefore, we propose a new mcts variant, called single-player monte-carlo tree search (sp-mcts). The selection and backpropagation strategy in sp-mcts are different from standard mcts. Moreover, sp-mcts makes use of a straightforward meta-search extension. We tested the method on the puzzle samegame. It turned out that our sp-mcts program gained the highest score so far on the standardized test set.
Original languageEnglish
Title of host publicationComputers and Games
Subtitle of host publication6th International Conference, CG 2008, Beijing, China, September 29 - October 1, 2008. Proceedings
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages1-12
Number of pages12
ISBN (Print)978-3-540-87608-3
DOIs
Publication statusPublished - 2008

Publication series

SeriesLecture Notes in Computer Science
Volume5131

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