Publication: Classifying efficiently the behavior of a Soccer team
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ISBN: 978-1-58603-887-8 (print)
ISBN: 978-1-60750-351-4 (online)
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2008
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IOS Press
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Abstract
In order to make a good decision, humans usually try to predict the behavior of others. By this prediction, many different tasks can be performed, such as to coordinate with them, to assist them or to predict their future behavior. In competitive domains, to recognize the behavior of the opponent can be very advantageous. In this paper, an approach for creating automatically the model of the behavior of a soccer team is presented. This approach is an effective and notable improvement of a previous work. As the actions performed by a soccer team are sequential, this sequentiality should be considered in the modeling process. Therefore, the observations of a soccer team in a dynamic, complex and continuous multi-variate world state are transformed into a sequence of atomic behaviors. Then, this sequence is analyzed in order to find out a model that defines the team behavior. Finally, the classification of an observed team is done by using a statistical test.
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Proceeding of: 10th International Conference on Intelligent Autonomous Systems (IAS 2008), Baden Baden, Germany, July 23-25th, 2008.
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Intelligent Autonomous Systems 10: IAS-10. IOS Press, 2008, pp. 316-323