Recognizing Formations in Opponent Teams Export

@incollection{citeulike:3424798, 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 {\pounds}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{\pounds}cial neural network and will be discussed in this paper. All soccer-clients are initialized with a speci{\pounds}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.}, author = {Visser, Ubbo and Dr\"{u}cker, Christian and H\"{u}bner, Sebastian and Schmidt, Esko and Weland, Hans-Georg}, citeulike-article-id = {3424798}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/3-540-45324-5_44}, doi = {10.1007/3-540-45324-5_44}, journal = {RoboCup 2000: Robot Soccer World Cup IV}, keywords = {formation, opponent-modelling, robocup}, pages = {391--396}, posted-at = {2008-10-17 17:04:04}, priority = {2}, title = {Recognizing Formations in Opponent Teams}, url = {http://dx.doi.org/10.1007/3-540-45324-5_44}, year = {2001} }

TY - CHAP ID - citeulike:3424798 L3 - citeulike-article-id:3424798 N2 - 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. JF - RoboCup 2000: Robot Soccer World Cup IV EP - 396 TI - Recognizing Formations in Opponent Teams SP - 391 KW - formation KW - opponent-modelling KW - robocup AU - Visser, Ubbo AU - Drücker, Christian AU - Hübner, Sebastian AU - Schmidt, Esko AU - Weland, Hans-Georg PY - 2001/// UR - http://dx.doi.org/10.1007/3-540-45324-5_44 ER -