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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Vydané v:	Applied soft computing Ročník 126; s. 109241
Hlavní autori:	Dayal, Aveen, Cenkeramaddi, Linga Reddy, Jha, Ajit
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.09.2022
Predmet:	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
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