MCTS Experiments on the Voronoi Game

Bruno Bouzy (1) , Marc Métivier (1) , Damien Pellier (1)

1 LIPADE - EA 2517 - Laboratoire d'Informatique Paris Descartes

Monte-Carlo Tree Search (MCTS) is a powerful tool in games with a finite branching factor. This paper describes an artificial player playing the Voronoi game, a game with an infinite branching factor. First, this paper shows how to use MCTS on a discretization of the Voronoi game, and the effects of enhancements such as RAVE and Gaussian processes (GP). A first set of experimental results shows that MCTS with UCB+RAVE or with UCB+GP are first good solutions for playing the Voronoi game without domain-dependent knowledge. Second, this paper shows how to greatly improve the playing level by using geometrical knowledge about Voronoi diagrams, the balance of diagrams being the key concept. The second set of experimental results shows that a player using MCTS and geometrical knowledge outperforms the player without knowledge.

Domaines: Intelligence artificielle [cs.AI]

Bruno Bouzy, Marc Métivier, Damien Pellier. MCTS Experiments on the Voronoi Game. International Conference on Advances in Computer Games, Nov 2011, Tilburg, Netherlands. ⟨10.1007/978-3-642-31866-5_9⟩. ⟨hal-01365573⟩