Reinforcement Learning Approaches for Multi-Agent Coordination in Wireless Networks and Smart Communication Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 13
Special Issue Editors
Interests: artificial intelligence; interactive cognitive technology
Special Issues, Collections and Topics in MDPI journals
Interests: electronic engineering; wireless communications; satellite-based data offloading
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The following Special Issue focuses on the integration of Multi-Agent Reinforcement Learning techniques into wireless networks and smart communication systems, with the aim of enhancing scalability, adaptability, and efficiency. By leveraging the capabilities of reinforcement learning in a multi-agent setting, communication systems can move toward fully autonomous and self-optimizing behavior, where individual agents learn to act both independently and cooperatively to achieve global objectives.
Dr. Yang Yi
Dr. Zhu Han
Guest Editors
Manuscript Submission Information
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Keywords
- multi-agent reinforcement learning
- wireless networks
- smart communication systems
- autonomous coordination
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