A Reinforcement Learning Approach Based on Automatic Policy Amendment for Multi-AUV Task Allocation in Ocean Current

A Reinforcement Learning Approach Based on Automatic Policy Amendment for Multi-AUV Task Allocation in Ocean Current

In this paper, the multiple autonomous underwater vehicles (AUVs) task allocation (TA) problem in ocean current environment based on a novel reinforcement learning approach is studied. First, the ocean current environment including direction and intensity is established and a reward function is desi...

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Hlavní autoři: Cheng Ding, Zhi Zheng
Médium: Článek
Jazyk:English
Vydáno: MDPI AG 2022-06-01
Edice:Drones
Témata:
multi-AUV
task allocation
reinforcement learning
policy automatic amendment
entropy
On-line přístup:https://www.mdpi.com/2504-446X/6/6/141

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https://www.mdpi.com/2504-446X/6/6/141

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