Living Reference Work Entry

Encyclopedia of Computer Graphics and Games

pp 1-6

Date: Latest Version

Monte-Carlo Tree Search

  • Mark H. M. WinandsAffiliated withDepartment of Data Science and Knowledge Engineering, Maastricht University Email author 


MCTS; Monte-Carlo Tree Search; UCT


Monte-Carlo Tree Search (MCTS) (Coulom 2007; Kocsis et al. 2006) is a best-first search method that does not require a positional evaluation function. It is based on a randomized exploration of the search space. Using the results of previous explorations, the algorithm gradually builds up a game tree in memory and successively becomes better at accurately estimating the values of the most promising moves. MCTS consists of four strategic steps, repeated as long as there is time left (Chaslot et al. 2008b). The steps, outlined in Fig. 1, are as follows:
Fig. 1

Outline of Monte-Carlo Tree Search (adapted from Chaslot et al. 2008b; Winands et al. 2010)

  1. 1.

    In the selection step, the tree is traversed from the root node downward until a state is chosen, which has not been stored in the tree.

  2. 2.

    Next, in the play-out step, moves are chosen in self-play until the end of the game is reached.

  3. 3.

    Subsequently, in the expansion step, one or more states e ...

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