Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

3 Oct 2016Ali YahyaAdrian LiMrinal KalakrishnanYevgen ChebotarSergey Levine

In principle, reinforcement learning and policy search methods can enable robots to learn highly complex and general skills that may allow them to function amid the complexity and diversity of the real world. However, training a policy that generalizes well across a wide range of real-world conditions requires far greater quantity and diversity of experience than is practical to collect with a single robot... (read more)

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