Abstract
Our long-term goal is to build a robot soccer team where the decision making part is based completely on Reinforcement Learning (RL) methods. The paper describes the overall approach pursued by the Karlsruhe Brainstormers simulator league team. Main parts of basic decision making are meanwhile solved using RL techniques. On the tactical level, first empirical results are presented for 2 against 2 attack situations.
Acknowledgements
We would like to thank the CMU-Team for providing parts of the source code of their competition team. In our current agent, we make use of their world model.
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References
A. G. Barto, S. J. Bradtke, and S. P. Singh. Learning to act using real-time dynamic programming. Artificial Intelligence, (72):81–138, 1995.
M. Lauer and M. Riedmiller. An algorithm for distributed reinforcement learning in cooperative multi-agent systems. In Proceedings of International Conference on Machine Learning, ICML’ 00, pages 535–542, Stanford, CA, 2000.
M. Riedmiller. Concepts and facilities of a neural reinforcement learning control architecture for technical process control. Journal of Neural Computing and Application, 8:323–338, 2000.
Peter Stone and Manuela Veloso. Team-partitioned, opaque-transition reinforcement learning. In M. Asada and H. Kitano, editors, RoboCup-98: Robot Soccer World Cup II. Springer Buch Verlag, 1998.
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© 2001 Springer-Verlag Berlin Heidelberg
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Riedmiller, M. et al. (2001). Karlsruhe Brainstormers - A Reinforcement Learning approach to robotic soccer. 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_40
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DOI: https://doi.org/10.1007/3-540-45324-5_40
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