Monte Carlo Tree Search (MCTS) is a heuristic search algorithm used for decision-making processes, most commonly in game-playing AI. It combines the concepts of Monte Carlo simulation and tree-based search to determine the most promising moves in games with large or complex search spaces, such as Go, Chess, and various video games.
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