Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations

Simulation-to-real transfer is an important strategy for making reinforcement learning practical with real robots. Successful sim-to-real transfer systems have difficulty producing policies which generalize across tasks, despite training for thousands of hours equivalent real robot time... (read more)

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