Mark H. M. Winands

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Monte-Carlo Tree Search (MCTS) is a new best-first search guided by the results of Monte-Carlo simulations. In this article we introduce two progressive strategies for MCTS, called progressive bias and progressive unpruning. They enable the use of relatively time-expensive heuristic knowledge without speed reduction. Progressive bias directs the search(More)
Monte-Carlo Tree Search (MCTS) is a new best-first search method that started a revolution in the field of Computer Go. Parallelizing MCTS is an important way to increase the strength of any Go program. In this article, we discuss three parallelization methods for MCTS: leaf parallelization, root parallelization, and tree parallelization. To be effective(More)
This paper proposes a new algorithm, called best reply search (BRS), for deterministic multiplayer games with perfect information. In BRS, only the opponent with the strongest counter move is allowed to make a move. More turns of the root player can be searched resulting in long-term planning. We test BRS in the games of Chinese Checkers, Focus, and(More)
Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. In this article we investigate the application of MCTS for the game Lines of Action (LOA). A new MCTS variant, called MCTS-Solver, has been designed to play narrow tactical lines better in sudden-death games such as LOA. The variant differs from the traditional(More)
Classical methods such as A* and IDA* are a popular and successful choice for one-player games. However, they fail without an accurate admissible evaluation function. In this paper 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)
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 (MCTS) is becoming increasingly popular for playing multi-player games. In this paper we propose two enhancements for MCTS in multi-player games: (1) Progressive History and (2) Multi-Player Monte-Carlo Tree Search Solver (MP-MCTS-Solver). We analyze the performance of these enhancements in two different multi-player games: Focus and(More)
NP-complete problems are a challenging task for researchers, who investigate tractable versions and attempt to generalise the methods used for solving them. Over the years a large set of successful standard methods have been developed. We mention A* and IDA* which have proven to be reasonably successful in solving a set of NP-complete problems, particularly(More)