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While reinforcement learning (RL) has the potential to enable robots to autonomously acquire a wide range of skills, in practice, RL usually requires manual, per-task engineering of reward functions, especially in real world settings where aspects of the environment needed to compute progress are not directly accessible.
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Ashley D Edwards · 2017
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Ashley D Edwards, Srijan Sood, and Charles L Isbell Jr · 2017
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Deep visual foresight for planning robot motion
Chelsea Finn and Sergey Levine · 2017
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Deep predictive policy training using reinforcement learning
Ali Ghadirzadeh, Atsuto Maki, Danica Kragic, and Mårten Björkman · 2017
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Amir Rosenfeld, Richard Zemel, and John K Tsotsos · 2018
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Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, and Chelsea Finn · 2018
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Annie Xie, Avi Singh, Sergey Levine, and Chelsea Finn · 2018
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