A Mahjong Game System Architecture Based on Empirical Knowledge

Imperfect-information game has always been the field that artificial intelligence computer game researchers want to crack. As a typical imperfect-information game, mahjong has also received extensive attention from researchers. This paper mainly takes mahjong as the research carrier, and proposes a mahjong game system architecture based on empirical knowledge, which mainly including professional mahjong game terms analysis, the design of mahjong computer game system and core game strategies. In the strategy, a combination of empirical algorithm and improved search tree algorithm is designed to formulate the player's game behavior in different periods. In the search tree algorithm, an evaluation function is constructed and a method to judge if the hand is in winning state is proposed. Finally, the experimental results show that the system architecture proposed in this article has a high level of game for the rules of popular mahjong, and it also has positive reference significance for other rules of mahjong game and imperfect-information items.