Safe Reinforcement Learning with Model Uncertainty Estimates
international conference on robotics and automation, 2019.
Many current autonomous systems are being designed with a strong reliance on black box predictions from deep neural networks (DNNs). However, DNNs tend to be overconfident in predictions on unseen data and can give unpredictable results for far-from-distribution test data. The importance of predictions that are robust to this distribution...More
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