Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
Artificial Intelligence
Team-Partitioned, Opaque-Transition Reinforced Learning
RoboCup-98: Robot Soccer World Cup II
Learning to act using real-time dynamic programming
Artificial Intelligence
Reliable Multi-robot Coordination Using Minimal Communication and Neural Prediction
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
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The following paper describes the design principles of decision making in the Karlruhe Brainstormers team that participated in the RoboCup Simulator League in Stockholm 1999. It is based on two basic ingredigents: the priority - probability - quality (PPQ) concept is a hybrid rule-based/ learning approach for tactical decisons, whereas the definition of goal-orientented moves allows to apply neural network based reinforcement learning techniques on the lower level.