Uncertainty-Aware Data Aggregation for Deep Imitation Learning

7 May 2019 Yuchen Cui David Isele Scott Niekum Kikuo Fujimura

Estimating statistical uncertainties allows autonomous agents to communicate their confidence during task execution and is important for applications in safety-critical domains such as autonomous driving. In this work, we present the uncertainty-aware imitation learning (UAIL) algorithm for improving end-to-end control systems via data aggregation... (read more)

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