Accelerating the training of deep reinforcement learning in autonomous driving

Volume: 10, Issue: 3, Pages: 649 - 656
Published: Sep 1, 2021
Abstract
Deep reinforcement learning has been successful in solving common autonomous driving tasks such as lane-keeping by simply using pixel data from the front view camera as input. However, raw pixel data contains a very high-dimensional observation that affects the learning quality of the agent due to the complexity imposed by a 'realistic' urban environment. Ergo, we investigate how compressing the raw pixel data from high-dimensional state to...
Paper Details
Title
Accelerating the training of deep reinforcement learning in autonomous driving
Published Date
Sep 1, 2021
Volume
10
Issue
3
Pages
649 - 656
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