Higher Order Statistics in Play-out Analysis

Playing out the game from the current state to the end many times randomly, provides statistics that can be used for selecting the best move. This play-out analysis has proved to work well in games such as Backgammon, Bridge, and Go. This paper introduces a method that selects relevant patterns of moves to collect higher order statistics. This can be used to improve the quality of the play outs. Play-out analysis avoids the horizon effect of regular game-tree search. The proposed method should be especially effective when the game can be decomposed into a number of subgames. Game of Y is a two-player board game played on a graph with a task of connecting three edges of the graph together. Preliminary experiments on Y did not yet show significant improvement over the first-order approach, but a door has been opened for further improvement. The game of Y might prove to be a good testbed for machine learning.