Monte Carlo Tree Search is a search algorithm that uses random simulations to evaluate possible actions in a decision tree. It balances exploration of uncertain choices with exploitation of promising choices and is used in planning, games, and reinforcement learning.
In computer science, Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes.