articleIEEE Transactions on Computational Intelligence and AI in GamesFeb 3, 2012Closed access

A Survey of Monte Carlo Tree Search Methods

CBCameron BrowneEJEdward J. PowleyDWDaniel WhitehouseSMSimon M. LucasPCPeter Cowling

Imperial College London · University of Bradford · +1 more institution

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Abstract

Monte Carlo tree search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the literature to date, intended to provide a snapshot of the state of the art after the first five years of MCTS research. We outline the core algorithm's derivation, impart some structure on the many variations and enhancements that have been proposed, and summarize the results from the key game and nongame domains to which MCTS methods have been applied. A number of…

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Topics & keywords

Topics
Keywords
  • Monte Carlo tree search
  • Computer science
  • Monte Carlo method
  • Snapshot (computer storage)
  • Generality
  • Tree (set theory)
  • Data mining
  • Machine learning
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