Query-Efficient Imitation Learning for End-to-End Autonomous Driving

20 May 2016Jiakai ZhangKyunghyun Cho

One way to approach end-to-end autonomous driving is to learn a policy function that maps from a sensory input, such as an image frame from a front-facing camera, to a driving action, by imitating an expert driver, or a reference policy. This can be done by supervised learning, where a policy function is tuned to minimize the difference between the predicted and ground-truth actions... (read more)

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