منابع مشابه
Monte-Carlo Tree Search
representation of the game. It was programmed in LISP. Further use of abstraction was also studied by Friedenbach (1980). The combination of search, heuristics, and expert systems led to the best programs in the eighties. At the end of the eighties a new type of Go programs emerged. These programs made an intensive use of pattern recognition. This approach was discussed in detail by Boon (1990)...
متن کاملParallel Monte-Carlo Tree Search
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 tree parallelization requires two techni...
متن کاملMonte-Carlo Tree Search Solver
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 MCTS in respect to backpropagation and se...
متن کاملMonte Carlo Tree Search in Imperfect-Information Games Doctoral Thesis
Monte Carlo Tree Search (MCTS) is currently the most popular game playing algorithm for perfect-information extensive-form games. Its adaptation led, for example, to human expert level Go playing programs or substantial improvement of solvers for domain-independent automated planning. Inspired by this success, researchers started to adapt this technique also for imperfect-information games. Imp...
متن کاملMonte-Carlo Tree Search using Batch Value of Perfect Information
This paper focuses on the selection phase of MonteCarlo Tree Search (MCTS). We define batch value of perfect information (BVPI) in game trees as a generalization of value of computation as proposed by Russell and Wefald, and use it for selecting nodes to sample in MCTS. We show that computing the BVPI is NP-hard, but it can be approximated in polynomial time. In addition, we propose methods tha...
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ژورنال
عنوان ژورنال: IEEE Transactions on Computational Intelligence and AI in Games
سال: 2012
ISSN: 1943-068X,1943-0698
DOI: 10.1109/tciaig.2012.2200894