Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks

20 Nov 2019Vibhavari DasagiRobert LeeJake BruceJürgen Leitner

Deep reinforcement learning has been shown to solve challenging tasks where large amounts of training experience is available, usually obtained online while learning the task. Robotics is a significant potential application domain for many of these algorithms, but generating robot experience in the real world is expensive, especially when each task requires a lengthy online training procedure... (read more)

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