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Monte Carlo Beam Search

Cazenave, Tristan (2012), Monte Carlo Beam Search, IEEE Transactions on Computational Intelligence and AI in Games, 4, 1, p. 68-72. 10.1109/TCIAIG.2011.2180723

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Type
Article accepté pour publication ou publié
Date
2012
Journal name
IEEE Transactions on Computational Intelligence and AI in Games
Volume
4
Number
1
Publisher
IEEE
Pages
68-72
Publication identifier
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Author(s)
Cazenave, Tristan
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
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.
Subjects / Keywords
Nested Monte-Carlo Search; Puzzle; Beam Search