Searching optimal movements in multi-player games with imperfect information
Kenshi Yoshimura, Teruhisa Hochin, Hiroki Nomiya · 2016
This paper proposes a search method of optimal movements in multi-player games with imperfect information in order to implement a Mahjong player exceeding human top players. The proposed method uses tabu search. It does not use the record of a game. Tabu search is applied to the states of discarding tiles and using the tile that other players discarded. The experiments were carried out in order to evaluate the proposed method. In the experiment of evaluating the rate of concordance of the usage of tiles, the maximum rate of concordance reached to 83%. This means effective winning hands could be found in the initial states. In the experiment of playing a game with benchmark players, it is shown that the proposed method is better than benchmark players. From these results, the possibility of the effective search of optimal solution by using tabu search was indicated.