The article presents the use of Monte Carlo Tree Search algorithms for the card game Lord of the Rings. The main challenge was the complexity of the game mechanics, in which each round consists of 5 decision stages and 2 random stages. To test various decision-making algorithms, a game simulator has been implemented. The research covered an agent based on expert rules, using flat Monte-Carlo search, as well as complete MCTS-UCB. Moreover different playout strategies has been compared. As a result of experiments, an optimal (assuming a limited time) combination of algorithms were formulated. The developed MCTS based method have demonstrated a advantage over agent with expert knowledge.
翻译:文章介绍了使用蒙特卡洛树搜索算法进行环王牌游戏。主要挑战在于游戏机学的复杂性,每轮由5个决定阶段和2个随机阶段组成。为了测试各种决策算法,已经实施了游戏模拟器。研究涵盖一个基于专家规则的代理人,使用蒙特-卡洛平坦的搜索,以及完整的 MCTS-UCB。此外,还比较了不同的玩耍策略。实验的结果是制定了一种最佳(假设时间有限)的算法组合。发达的MCTS法比具有专门知识的代理人更有利。