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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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