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Policy Learning – A Unified Perspective with Applications in Robotics
[chapter]
2008
Lecture Notes in Computer Science
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
doi:10.1007/978-3-540-89722-4_17
fatcat:ypyvk5detbagblvkfpclloxdia