A survey on policy search algorithms for learning robot controllers in a handful of trials

6 Jul 2018 • Konstantinos Chatzilygeroudis • Vassilis Vassiliades • Freek Stulp • Sylvain Calinon • Jean-Baptiste Mouret

Most policy search algorithms require thousands of training episodes to find an effective policy, which is often infeasible with a physical robot. This survey article focuses on the extreme other end of the spectrum: how can a robot adapt with only a handful of trials (a dozen) and a few minutes?.. (read more)

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