Collaborative task decision-making of multi-UUV in dynamic environments based on deep reinforcement learning-Reference-Cited by-同舟云学术

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Collaborative task decision-making of multi-UUV in dynamic environments based on deep reinforcement learning

Published:2024-08-22 Issue: Volume: Page:1-11
ISSN:1744-5302
Container-title:Ships and Offshore Structures
language:en
Short-container-title:Ships and Offshore Structures

Author:

Yu Haomiao¹^ORCID,Zhang Sijie¹

Affiliation:

1. College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China

Funder

National Natural Science Foundation of China

Liaoning Province Applied Basic Research Program Project

National Basic Research Program Project

Fundamental Research Funds for the Central Universities

Dalian Science and Technology Innovation Fund Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17445302.2024.2391788

Reference34 articles.

1. Reinforcement Learning Based Obstacle Avoidance for Autonomous Underwater Vehicle

2. Caicedo JC Lazebnik S. 2015. Active object localization with deep reinforcement learning. In: Proceedings of the IEEE International Conference on Computer Vision; Santiago Chile. p. 2488–2496.

3. Concise deep reinforcement learning obstacle avoidance for underactuated unmanned marine vessels

4. Neural networks based reinforcement learning for mobile robots obstacle avoidance

5. Foerster J Assael IA De Freitas N Whiteson S. 2016. Learning to communicate with deep multi-agent reinforcement learning. In: Advances in neural information processing systems 29.

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