Monte Carlo method is even used by chess programs. Having the engine quickly play multiple games against itself, from a given position, is an alternative method of evaluation, probing how the position holds "in practice".
Also Monte Carlo Tree Search was decisive in bringing Go (the ancient board game) engines from unable to compete with advanced amateur players to successfully competing with the cream of the pros!
I find it remarkable how well MCTS works. Even without the value or policy net, the vanilla algorithm is capable of finding meaningful results by solving the MDP.
