Reward criteria impact on the performance of reinforcement learning agent for autonomous navigation

In reinforcement learning, an agent takes action at every time step (follows a policy) in an environment to maximize the expected cumulative reward. Therefore, the shaping of a reward function plays a crucial role in an agent’s learning. Designing an optimal reward function is not a trivial task. In...

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Bibliographic Details

Published in:	Applied soft computing Vol. 126; p. 109241
Main Authors:	Dayal, Aveen, Cenkeramaddi, Linga Reddy, Jha, Ajit
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.09.2022
Subjects:	Autonomous navigation Deep reinforcement learning Machine learning and artificial intelligence Reward criteria Deep reinforcement learning Autonomous navigation Reward criteria Machine learning and artificial intelligence
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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