Objective Mismatch in Model-based Reinforcement Learning

ICLR 2020 Nathan LambertBrandon AmosOmry YadanRoberto Calandra

Model-based reinforcement learning (MBRL) has been shown to be a powerful framework for data-efficiently learning control of continuous tasks. Recent work in MBRL has mostly focused on using more advanced function approximators and planning schemes, with little development of the general framework... (read more)

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