An Improved Dueling Deep Double-Q Network Based on Prioritized Experience Replay for Path Planning of Unmanned Surface Vehicles

An Improved Dueling Deep Double-Q Network Based on Prioritized Experience Replay for Path Planning of Unmanned Surface Vehicles

Unmanned Surface Vehicle (USV) has a broad application prospect and autonomous path planning as its crucial technology has developed into a hot research direction in the field of USV research. This paper proposes an Improved Dueling Deep Double-Q Network Based on Prioritized Experience Replay (IPD3Q...

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Bibliographic Details
Main Authors: Zhengwei Zhu, Can Hu, Chenyang Zhu, Yanping Zhu, Yu Sheng
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Journal of Marine Science and Engineering
Subjects:
deep reinforcement learning
unmanned surface vehicle
path planning
algorithm optimization
fusion and integration
Online Access:https://www.mdpi.com/2077-1312/9/11/1267

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