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MCTS Experiments on the Voronoi Game

  • Bruno Bouzy
  • Marc Métivier
  • Damien Pellier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7168)

Abstract

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

Keywords

Gaussian Process Voronoi Diagram Gravity Center Balance Cell Bandit Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bruno Bouzy
    • 1
  • Marc Métivier
    • 1
  • Damien Pellier
    • 1
  1. 1.LIPADEUniversité Paris DescartesFrance

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