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Best of Playout 2015 - Monte Carlo tree search - Netflix
In computer science, Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in game play. Two leading examples of Monte Carlo tree search are the computer game Total War: Rome II's implementation in their high level campaign AI and recent computer Go programs, followed by chess and shogi, as well as real-time video games and games with incomplete information such as poker (see history section).
Best of Playout 2015 - Advantages and disadvantages - Netflix
Although it has been proven that the evaluation of moves in Monte Carlo tree search converges to minimax, the basic version of Monte Carlo tree search converges very slowly. However Monte Carlo tree search does offer significant advantages over alpha–beta pruning and similar algorithms that minimize the search space. In particular, Monte Carlo tree search does not need an explicit evaluation function. Simply implementing the game's mechanics is sufficient to explore the search space (i.e. the generating of allowed moves in a given position and the game-end conditions). As such, Monte Carlo tree search can be employed in games without a developed theory or in general game playing. The game tree in Monte Carlo tree search grows asymmetrically as the method concentrates on the more promising subtrees. Thus it achieves better results than classical algorithms in games with a high branching factor. Moreover, Monte Carlo tree search can be interrupted at any time yielding the most promising move already found. A disadvantage is that, faced in a game with an expert player, there may be a single branch which leads to a loss. Because this is not easily found at random, the search may not “see” it and will not take it into account. It is believed that this may have been part of the reason for AlphaGo's loss in its fourth game against Lee Sedol. In essence, the search attempts to prune sequences which are less relevant. In some cases, a play can lead to a very specific line of play which is significant, but which is overlooked when the tree is pruned, and this outcome is therefore “off the search radar”.
Best of Playout 2015 - References - Netflix