Monte Carlo Tree Search in Simultaneous Move Games with Applications to Goofspiel

  title={Monte Carlo Tree Search in Simultaneous Move Games with Applications to Goofspiel},
  author={Marc Lanctot and Viliam Lis{\'y} and Mark H. M. Winands},
Monte Carlo Tree Search (MCTS) has become a widely popular sampled-based search algorithm for two-player games with perfect information. When actions are chosen simultaneously, players may need to mix between their strategies. In this paper, we discuss the adaptation of MCTS to simultaneous move games. We introduce a new algorithm, Online Outcome Sampling (OOS), that approaches a Nash equilibrium strategy over time. We compare both head-to-head performance and exploitability of several MCTS… CONTINUE READING


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Publications referenced by this paper.
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Cadia-player: A general game playing agent. Master’s thesis, Reyk- jav́ık

H. Finnsson
View 15 Excerpts
Highly Influenced

Gambling in a rigged casino: The adversarial multi-armed bandit problem

Electronic Colloquium on Computational Complexity • 1995
View 13 Excerpts
Highly Influenced

Monte Carlo Sampling and Regret Minimization for Equilibrium Computation and Decision-Making in Large Extensive Form Games

M. Lanctot
Ph.D. the- sis, Department of Computing Science, • 2013
View 4 Excerpts
Highly Influenced

Simulation-Based General Game Playing

H. Finnsson
Ph.D. thesis, Reykjav́ık University • 2012
View 3 Excerpts
Highly Influenced

A Survey of Monte Carlo Tree Search Methods

IEEE Transactions on Computational Intelligence and AI in Games • 2012
View 1 Excerpt

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