What do you understand by Monte Carlo Tree Search? Explain.

Monte Carlo Tree Search (MCTS) is a heuristic search algorithm used in decision processes, particularly in artificial intelligence, to efficiently explore and evaluate the vast search space of possible moves in a game or decision-making problem. It has found applications in various domains, including board games like Chess, Go, and video games, as well as optimization and planning problems.

At its core, MCTS combines elements of random sampling (Monte Carlo) and tree search techniques to guide its exploration of the search space towards promising regions where optimal decisions are likely to be found. Unlike traditional tree search algorithms such as Minimax, which exhaustively explore all possible moves up to a certain depth, MCTS focuses on ________ ___ __________ __________ __________ ____ __________ _______ ______ ___ _______.
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