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INFIFORCE Intelligent Technology, Carnegie Mellon University, The University of Hong Kong, Princeton University Princeton University Carnegie Mellon University
CMU Machine Learning2
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Extracting temporal geometry from generative models can boost reinforcement learning performance by over 2x without changing the optimal policy.
Forget hand-engineered reward functions: this method learns complex exploratory behaviors by simply predicting which states lead to unpredictable futures.
