Calibrated Model-Based Deep Reinforcement Learning

19 Jun 2019Ali MalikVolodymyr KuleshovJiaming SongDanny NemerHarlan SeymourStefano Ermon

Estimates of predictive uncertainty are important for accurate model-based planning and reinforcement learning. However, predictive uncertainties---especially ones derived from modern deep learning systems---can be inaccurate and impose a bottleneck on performance... (read more)

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