Classifying the Strategies of an Opponent Team Based on a Sequence of Actions in the RoboCup SSL
In this paper, we propose a new method for classifying the strategies of an opponent in the RoboCup Soccer Small-Size League. Each strategy generates a sequence of basic actions selected from a kick action, a mark action, or other similar actions. Here, we identify strategies by classifying an observed sequences of basic actions selected by an opponent during a game. This method greatly improves our previous method  in the following two ways: the previous method was applicable mainly to set plays, whereas this restriction is lifted in our new method. Additionally, our new method requires a lower computational time than the previous method. Assuming that our team was the opponent team, our team’s strategies were evaluated using the Rand Index, yielding a value exceeding 0.877 in 3 out of 4 games. A Rand index value exceeding 0.840 was obtained from an analysis of the 4 opponent teams (1 game for each opponent team). These Rand indices represent a high level of classification algorithm performance.
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