Analyzing and Learning an Opponent's Strategies in the RoboCup Small Size League
Analyzing and Learning an Opponent's Strategies in the RoboCup Small Size League
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RoboCup 小规模联赛中对手策略的分析和学习
DOI：
10.1007/978-3-662-44468-9_15
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
T. Naruse
中科院分区：
文献类型：
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作者：
Kotaro Yasui;Kunikazu Kobayashi;K. Murakami;T. Naruse
本文提出了一个用于分析和学习机器人足球比赛中对手策略的不相似函数。这里给出的dissimilarity函数标识了对手部署选择的两个实例之间的差异。开发了该函数的扩展，以进一步确定在两个单独的时间间隔内部署选择之间的差异。不相似函数生成不相似矩阵，然后利用聚类分析对对手的策略进行分析和分类。分类步骤是通过分析在2012年机器人世界杯期间小型联赛比赛中获得的记录数据中捕获的对手在定局中使用的策略来实现的。实验结果表明，该方法可以有效地对套路进攻策略进行分类。讨论了在实际比赛中学习对手的进攻策略并将队友部署在有利位置的方法。
This paper proposes a dissimilarity function that is useful for analyzing and learning the opponent’s strategies implemented in a RoboCup Soccer game. The dissimilarity function presented here identifies the differences between two instances of the opponent’s deployment choices. An extension of this function was developed to further identify the differences between deployment choices over two separate time intervals. The dissimilarity function, which generates a dissimilarity matrix, is then exploited to analyze and classify the opponent’s strategies using cluster analysis. The classification step was implemented by analyzing the opponent’s strategies used in set plays captured in the logged data obtained from the Small Size League’s games played during RoboCup 2012. The experimental results showed that the attacking strategies used in set plays may be effectively classified. A method for learning an opponent’s attacking strategies and deploying teammates in advantageous positions on the fly in actual games is discussed.