Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning

Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning

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In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication...

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Bibliographic Details
Main Authors: Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2022-08-01
Series:Tongxin xuebao
Subjects:
emergency communication;coverage optimization;multi-agent reinforcement learning;distributed training
Online Access:http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2022131
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