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2008

Policy Learning - A Unified Perspective with Applications in Robotics

9 years 1 hour ago
Policy Learning - A Unified Perspective with Applications in Robotics
Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper, we show two contributions: firstly, we show a unified perspective which allows us to derive several policy learning algorithms from a common point of view, i.e, policy gradient algorithms, naturalgradient algorithms and EM-like policy learning. Secondly, we present several applications to both robot motor primitive learning as well as to robot control in task space. Results both from simulation and several different real robots are shown.
Jan Peters, Jens Kober, Duy Nguyen-Tuong
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where EWRL
Authors Jan Peters, Jens Kober, Duy Nguyen-Tuong
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