Title :
Monte Carlo Beam Search
Author :
Cazenave, Tristan
Author_Institution :
LAMSADE, Univ. Paris-Dauphine, Paris, France
fDate :
3/1/2012 12:00:00 AM
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;
Journal_Title :
Computational Intelligence and AI in Games, IEEE Transactions on
DOI :
10.1109/TCIAIG.2011.2180723