Abstract
The online coach within the simulation league has become more powerful over the last few years. Therefore, new options with regard to the recognition of the opponents strategy are possible. For example, the online coach is the only player who gets the information of all the objects on the £eld. This leads to the idea determine the opponents play system by the online coach and then choose an effective counter-strategy. This has been done with the help of an arti£cial neural network and will be discussed in this paper. All soccer-clients are initialized with a speci£c behavior and can change their behavior to an appropriate mode depending on the coach’s commands. The result is a ¤exible and effective game played by the eleven soccer-clients.
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Visser, U., Drücker, C., Hübner, S., Schmidt, E., Weland, HG. (2001). Recognizing Formations in Opponent Teams. In: Stone, P., Balch, T., Kraetzschmar, G. (eds) RoboCup 2000: Robot Soccer World Cup IV. RoboCup 2000. Lecture Notes in Computer Science(), vol 2019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45324-5_44
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