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Emergence of Cooperative Tactics by Soccer Agents with Ability of Prediction and Learning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2159))

Abstract

This paper describes soccer agents that can learn by themselves to make use of emergent cooperative tactics. Considering the methods that actual coaches of soccer help their players to learn the way of good play, we developed a mechanism of learning to distinguish good tactics from bad ones. The agents adaptively learned the utilities of the situations and the conditional probabilities about the situations in order to predict the opponents’ behavior and in order to select good actions. The agents cooperatively created some combinations of passes, such as a wall pass and a one-two pass which we had never taught in advance how to execute.

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References

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  5. Eiji Uchibe, Masateru Nakamura, and Minoru Asada. Co-evolution for Cooperative Behavior Acquisition in a Multiple Mobile Robot Environment. Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 1998 (IROS’ 98), pp. 425–430, 1998.

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© 2001 Springer-Verlag Berlin Heidelberg

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Kumada, Y., Ueda, K. (2001). Emergence of Cooperative Tactics by Soccer Agents with Ability of Prediction and Learning. In: Kelemen, J., Sosík, P. (eds) Advances in Artificial Life. ECAL 2001. Lecture Notes in Computer Science(), vol 2159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44811-X_61

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  • DOI: https://doi.org/10.1007/3-540-44811-X_61

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42567-0

  • Online ISBN: 978-3-540-44811-2

  • eBook Packages: Springer Book Archive

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