Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning
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...
Saved in:
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: | |
Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022131/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Reinforcement Learning-Based Autonomous Soccer Agents: A Study in Multi-Agent Coordination and Strategy Development
by: Biplov Paneru, et al.
Published: (2025-01-01) -
Multi mobile agent itinerary planning based on network coverage and multi-objective discrete social spider optimization algorithm
by: Zhou-zhou LIU, et al.
Published: (2017-06-01) -
Research and application of air-to-ground continuous coverage technology for air-space emergency communication system
by: Shengwei CHEN, et al.
Published: (2022-08-01) -
Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning
by: Anatolii Borzilov, et al.
Published: (2025-01-01) -
Multi-Agent Hierarchical Graph Attention Actor–Critic Reinforcement Learning
by: Tongyue Li, et al.
Published: (2024-12-01)