2012 ASurveyofMonteCarloTreeSearchMe
- (Browne et al., 2012) ⇒ Cameron B Browne, Edward Powley, Daniel Whitehouse, Simon M Lucas, Peter I Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis, and Simon Colton. (2012). “A Survey of Monte Carlo Tree Search Methods.” In: Computational Intelligence and AI in Games, IEEE Transactions on, 4(1). doi:10.1109/TCIAIG.2012.2186810
Subject Headings: Monte Carlo Tree Search (MCTS).
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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 open research questions indicate that the field is ripe for future work.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2012 ASurveyofMonteCarloTreeSearchMe | Cameron B Browne Edward Powley Daniel Whitehouse Simon M Lucas Peter I Cowling Philipp Rohlfshagen Stephen Tavener Diego Perez Spyridon Samothrakis Simon Colton | A Survey of Monte Carlo Tree Search Methods | 10.1109/TCIAIG.2012.2186810 | 2012 |