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Model-based reinforcement learning is a promising learning strategy for practical robotic applications due to its improved data-efficiency versus model-free counterparts.
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Anusha Nagabandi, Gregory Kahn, Ronald Fearing and Sergey Levine · 2018
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Himanshu Sahni, Toby Buckley, Pieter Abbeel and Ilya Kuzovkin · 2019
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Anusha Nagabandi, Kurt Konolige, Sergey Levine and Vikash Kumar · 2020
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Qiwei He, Liansheng Zhuang and Houqiang Li · 2020
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