Book Chapter or Conference Paper Title
Opponent classification in robot soccer
Faculty / School
Faculty of Computer Sciences (FCS)
Department of Computer Science
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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems
Seoul, Korea (Republic of)
10-12 June 2015
Springer, Berlin, Heidelberg
Abstract / Description
The paper presents an approach to perform post-hoc analysis of RoboCup Soccer Simulation 3D teams via log files of their matches and to learn a model to classify them not only as being strong, medium or weak but also through their game playing styles such as frequent kickers, frequent dribblers, heavy/lean attackers, etc. The learned model can then be used to further cluster teams to predict game style of similar opponents. We have applied the presented approach to 22 teams from RoboCup 2011 in a fully automated fashion and the results show the validity of our approach.
Larik, A. S., & Haider, S. (2015, June). Opponent classification in robot soccer. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (pp. 478-487). Springer, Cham.
Larik, A. S., & Haider, S. (2015). Opponent classification in robot soccer., 9101, 478-487. https://doi.org/10.1007/978-3-319-19066-2_46