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In this paper, we deal with the reality gap from a novel perspective, targeting transferring Deep Reinforcement Learning (DRL) policies learned in simulated environments to the real-world domain for visual control tasks.
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J. Zhang, J. T. Springenberg, J. Boedecker, and W. Burgard, “Deep reinforcement learning with successor features for navigation across similar environments,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , Sept 2017, pp. 2371–2378
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