Learn More
—The aim of General Game Playing (GGP) is to create programs capable of playing a wide range of different games at an expert level, given only the rules of the game. The most successful GGP programs currently employ simulation-based Monte-Carlo Tree Search (MCTS). The performance of MCTS depends heavily on the simulation strategy used. In this paper we(More)
Classic methods such as A* and IDA* are a popular and successful choice for one-player games. However, without an accurate admissible evaluation function , they fail. In this article we investigate whether Monte-Carlo Tree Search (MCTS) is an interesting alternative for one-player games where A* and IDA* methods do not perform well. Therefore, we propose a(More)
Monte-Carlo Tree Search is a best-first search technique based on simulations to sample the state space of a decision-making problem. In games, positions are evaluated based on estimates obtained from rewards of numerous randomized play-outs. Generally, rewards from play-outs are discrete values representing the outcome of the game (loss, draw, or win),(More)
—Monte Carlo Tree Search (MCTS) is a widely-used technique for game-tree search in sequential turn-based games. The extension to simultaneous move games, where all players choose moves simultaneously each turn, is non-trivial due to the complexity of this class of games. In this paper, we describe simultaneous move MCTS and analyze its application in a set(More)
  • 1