Learning to Explore in Motion and Interaction Tasks

10 Aug 2019Miroslav BogdanovicLudovic Righetti

Model free reinforcement learning suffers from the high sampling complexity inherent to robotic manipulation or locomotion tasks. Most successful approaches typically use random sampling strategies which leads to slow policy convergence... (read more)

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