Application of UCT Search to the Connection Games of Hex, Y, *Star, and Renkula!
Application of UCT Search to the Connection Games of Hex, Y, *Star, and Renkula!
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UCT搜索在Hex、Y、*Star、Renkula连线游戏中的应用！
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
J. Peltonen
中科院分区：
文献类型：
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作者：
T. Raiko;J. Peltonen
在许多棋类游戏中，博弈分析已被证明是人工智能（AI）的一种成功方法。我们的想法是从当前状态到结束进行多次游戏，每次游戏都是随机的;然后通过分析一组游戏及其结果来选择一个好的下一步。在本文中，我们应用播放分析所谓的“连接游戏”，抽象的棋盘游戏，件的连接是很重要的。在这类游戏中，评估游戏状态是困难的，并且基于标准字母搜索的AI不能很好地工作。相反，我们使用UCT search，这是一种播放分析方法，其中前瞻树中的第一步移动被视为多目标强盗问题，其余的播放使用随机播放。我们在四个不同的连接游戏中测试了UCT的有效性，其中包括一个名为R nkula！的新颖游戏。
Play-out analysis has proved a succesful approach for artifi cial intelligence (AI) in many board games. The idea is to play numerous times from the current state to th e end, with randomness in each play-out; a good next move is then chosen by analyzing the set of play-ou ts and their outcomes. In this paper we apply play-out analysis to so-called ‘connection games’ , abstract board games where connectivity of pieces is important. In this class of games, evaluating th e game state is difficult and standard alphabeta search based AI does not work well. Instead, we use UCT se arch, a play-out analysis method where the first moves in the lookahead tree are seen as multi-a rmed bandit problems and the rest of the play-out is played randomly using heuristics. We demons trate the effectiveness of UCT in four different connection games, including a novel game called R nkula!.