The article presents research on the use of Monte-Carlo Tree Search (MCTS) methods to create an artificial player for the popular card game "The Lord of the Rings". The game is characterized by complicated rules, multi-stage round construction, and a high level of randomness. The described study found that the best probability of a win is received for a strategy combining expert knowledge-based agents with MCTS agents at different decision stages. It is also beneficial to replace random playouts with playouts using expert knowledge. The results of the final experiments indicate that the relative effectiveness of the developed solution grows as the difficulty of the game increases.
翻译:文章介绍了关于使用蒙特卡洛树搜索(MCTS)方法为流行牌游戏“环之王”创造一个人造玩家的研究。游戏的特点是规则复杂、多阶段圆轮构造和高度随机性。所述研究发现,将专家知识型代理与处于不同决策阶段的MCTS代理结合起来的战略最有可能获胜。用专家知识来取代随机玩耍也是有益的。最后实验的结果显示,随着游戏难度的增加,开发的解决方案的相对有效性会增加。