A Multi-Ship Collision Avoidance Algorithm Using Data-Driven Multi-Agent Deep Reinforcement Learning

Maritime Autonomous Surface Ships (MASS) are becoming of interest to the maritime sector and are also on the agenda of the International Maritime Organization (IMO). With the boom in global maritime traffic, the number of ships is increasing rapidly. The use of intelligent technology to achieve auto...

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Bibliographic Details
Published in:	Journal of marine science and engineering Vol. 11; no. 11; p. 2101
Main Authors:	Niu, Yihan, Zhu, Feixiang, Wei, Moxuan, Du, Yifan, Zhai, Pengyu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2023
Subjects:	Algorithms Artificial intelligence Avoidance behaviour Collision avoidance Collisions Collisions at sea Cooperation Data collection data-driven Decision making Deep learning Design Hazardous areas International regulations Learning Literature reviews Machine learning MADRL Maritime industry MASS multi-ship autonomous collision avoidance decision-making Multiagent systems Neural networks Reinforcement Ship accidents & safety Shipping industry Ships Simulation Traffic information Unknown environments
ISSN:	2077-1312, 2077-1312
Online Access:	Get full text
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