Monte Carlo tree search - Wikipedia, the free encyclopedia

In computer science, Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in game play. A leading example is recent computer Go programs,[1] but it also has been used in other board games, as well as real-time video games and non-deterministic games such as poker (see history section). The focus of Monte Carlo tree search is on the analysis of the most promising moves, expanding the search tree based on random sampling of the search space. The application of Monte Carlo tree search in games is based on many playouts. In each playout, the game is played-out to the very end by selecting moves at random.