Reinforcement Learning for Humanoid Robotics

@inproceedings{Peters2003ReinforcementLF,
  title={Reinforcement Learning for Humanoid Robotics},
  author={Jan Peters and Sethu Vijayakumar and Stefan Schaal},
  year={2003}
}
Reinforcement learning offers one of the most general framework to take traditional robotics towards true autonomy and versatility. However, applying reinforcement learning to high dimensional movement systems like humanoid robots remains an unsolved problem. In this paper, we discuss different approaches of reinforcement learning in terms of their applicability in humanoid robotics. Methods can be coarsely classified into three different categories, i.e., greedy methods, ‘vanilla’ policy… CONTINUE READING
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6 Excerpts

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