DocumentCode
1469279
Title
Monte Carlo Beam Search
Author
Cazenave, Tristan
Author_Institution
LAMSADE, Univ. Paris-Dauphine, Paris, France
Volume
4
Issue
1
fYear
2012
fDate
3/1/2012 12:00:00 AM
Firstpage
68
Lastpage
72
Abstract
Monte Carlo tree search is the state of the art for multiple games and for solving puzzles such as Morpion Solitaire. Nested Monte Carlo (NMC) search is a Monte Carlo tree search algorithm that works well for solving puzzles. We propose to enhance NMC search with beam search. We test the algorithm on Morpion Solitaire. Thanks to beam search, our program has been able to match the record score of 82 moves. Monte Carlo beam search achieves better scores in less time than NMC search alone.
Keywords
Monte Carlo methods; computational complexity; computer games; tree searching; Monte Carlo beam search; Monte Carlo tree search algorithm; Morpion solitaire; nested Monte Carlo search; puzzle solving; Computer science; Computers; Games; Learning systems; Monte Carlo methods; Vegetation; Beam search; nested Monte Carlo (NMC) search; puzzle;
fLanguage
English
Journal_Title
Computational Intelligence and AI in Games, IEEE Transactions on
Publisher
ieee
ISSN
1943-068X
Type
jour
DOI
10.1109/TCIAIG.2011.2180723
Filename
6169183
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