Autonomous underwater vehicle formation control and obstacle avoidance using multi-agent generative adversarial imitation learning-Reference-Cited by-同舟云学术

Autonomous underwater vehicle formation control and obstacle avoidance using multi-agent generative adversarial imitation learning

Published:2022-10 Issue: Volume:262 Page:112182
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Fang Zheng,Jiang Dong,Huang Jie^ORCID,Cheng Chunxi,Sha Qixin,He Bo,Li Guangliang^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Ocean Engineering,Environmental Engineering

Reference49 articles.

1. Deep reinforcement learning: A brief survey;Arulkumaran;IEEE Signal Process. Mag.,2017

2. A comprehensive survey of multiagent reinforcement learning;Busoniu;IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.),2008

3. A new framework for multi-agent reinforcement learning–centralized training and exploration with decentralized execution via policy distillation;Chen,2019

4. Path planning and obstacle avoidance for AUV: A review;Cheng;Ocean Eng.,2021

5. Generative adversarial networks: An overview;Creswell;IEEE Signal Process. Mag.,2018

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