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Fast approximate max-n Monte Carlo tree search for Ms Pac-Man

Samothrakis, S and Robles, D and Lucas, S (2011) 'Fast approximate max-n Monte Carlo tree search for Ms Pac-Man.' IEEE Transactions on Computational Intelligence and AI in Games, 3 (2). 142 - 154. ISSN 1943-068X

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We present an application of Monte Carlo tree search (MCTS) for the game of Ms Pac-Man. Contrary to most applications of MCTS to date, Ms Pac-Man requires almost real-time decision making and does not have a natural end state. We approached the problem by performing Monte Carlo tree searches on a five player maxn tree representation of the game with limited tree search depth. We performed a number of experiments using both the MCTS game agents (for pacman and ghosts) and agents used in previous work (for ghosts). Performance-wise, our approach gets excellent scores, outperforming previous non-MCTS opponent approaches to the game by up to two orders of magnitude. © 2011 IEEE.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 19 Oct 2012 15:44
Last Modified: 13 Feb 2019 11:15

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