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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Kaiqing Zhang, Zhuoran Yang, Tamer Başar
Studies in systems, decision and control (2021), pp. 321-384
Closed Access | Times Cited: 719

Showing 1-25 of 719 citing articles:

Multi-agent deep reinforcement learning: a survey
Sven Gronauer, Klaus Diepold
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 895-943
Open Access | Times Cited: 443
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications
Khaled B. Letaief, Yuanming Shi, Jianmin Lu, et al.
IEEE Journal on Selected Areas in Communications (2021) Vol. 40, Iss. 1, pp. 5-36
Open Access | Times Cited: 405
Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing
Wei Xu, Zhaohui Yang, Derrick Wing Kwan Ng, et al.
IEEE Journal of Selected Topics in Signal Processing (2023) Vol. 17, Iss. 1, pp. 9-39
Open Access | Times Cited: 298
Reinforcement Learning based Recommender Systems: A Survey
M. Mehdi Afsar, Trafford Crump, Behrouz H. Far
ACM Computing Surveys (2022) Vol. 55, Iss. 7, pp. 1-38
Open Access | Times Cited: 287
Applications of reinforcement learning in energy systems
A.T.D. Perera, Parameswaran Kamalaruban
Renewable and Sustainable Energy Reviews (2020) Vol. 137, pp. 110618-110618
Open Access | Times Cited: 264
A review of cooperative multi-agent deep reinforcement learning
Afshin Oroojlooy, Davood Hajinezhad
Applied Intelligence (2022) Vol. 53, Iss. 11, pp. 13677-13722
Closed Access | Times Cited: 240
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial
Amal Feriani, Ekram Hossain
IEEE Communications Surveys & Tutorials (2021) Vol. 23, Iss. 2, pp. 1226-1252
Open Access | Times Cited: 231
Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges
Xin Chen, Guannan Qu, Yujie Tang, et al.
IEEE Transactions on Smart Grid (2022) Vol. 13, Iss. 4, pp. 2935-2958
Open Access | Times Cited: 210
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications
Jihong Park, Sumudu Samarakoon, Anis Elgabli, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 796-819
Open Access | Times Cited: 175
Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles
Sikai Chen, Jiqian Dong, Paul Ha, et al.
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 36, Iss. 7, pp. 838-857
Closed Access | Times Cited: 167
A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems
Rafael Figueiredo Prudencio, Marcos R. O. A. Máximo, Esther Luna Colombini
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 8, pp. 10237-10257
Open Access | Times Cited: 133
Multi-UAV Path Planning for Wireless Data Harvesting With Deep Reinforcement Learning
Harald Bayerlein, Mirco Theile, Marco Caccamo, et al.
IEEE Open Journal of the Communications Society (2021) Vol. 2, pp. 1171-1187
Open Access | Times Cited: 121
Federated reinforcement learning: techniques, applications, and open challenges
Jiaju Qi, Qihao Zhou, Lei Lei, et al.
(2021)
Open Access | Times Cited: 114
Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
Tianxu Li, Kun Zhu, Nguyen Cong Luong, et al.
IEEE Communications Surveys & Tutorials (2022) Vol. 24, Iss. 2, pp. 1240-1279
Closed Access | Times Cited: 97
Cooperative and Competitive Multi-Agent Systems: From Optimization to Games
Jianrui Wang, Yitian Hong, Jiali Wang, et al.
IEEE/CAA Journal of Automatica Sinica (2022) Vol. 9, Iss. 5, pp. 763-783
Closed Access | Times Cited: 84
A Transcoding-Enabled 360° VR Video Caching and Delivery Framework for Edge-Enhanced Next-Generation Wireless Networks
Han Xiao, Changqiao Xu, Zichen Feng, et al.
IEEE Journal on Selected Areas in Communications (2022) Vol. 40, Iss. 5, pp. 1615-1631
Closed Access | Times Cited: 78
Deep multiagent reinforcement learning: challenges and directions
Annie Wong, Thomas Bäck, Anna V. Kononova, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5023-5056
Open Access | Times Cited: 76
Democracy by Design: Perspectives for Digitally Assisted, Participatory Upgrades of Society
Dirk Helbing, Sachit Mahajan, Regula Hänggli, et al.
Journal of Computational Science (2023) Vol. 71, pp. 102061-102061
Open Access | Times Cited: 50
Reinforcement Learning Methods for Computation Offloading: A Systematic Review
Zeinab Zabihi, Amir Masoud Eftekhari Moghadam, Mohammad Hossein Rezvani
ACM Computing Surveys (2023) Vol. 56, Iss. 1, pp. 1-41
Closed Access | Times Cited: 50
Artificial Intelligence in 6G Wireless Networks: Opportunities, Applications, and Challenges
Abdulraqeb Alhammadi, Ibraheem Shayea, Ayman A. El‐Saleh, et al.
International Journal of Intelligent Systems (2024) Vol. 2024, pp. 1-27
Closed Access | Times Cited: 20
Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges
Giorgio Franceschelli, Mirco Musolesi
Journal of Artificial Intelligence Research (2024) Vol. 79, pp. 417-446
Open Access | Times Cited: 19
Advancements and future outlook of Artificial Intelligence in energy and climate change modeling
Mobolaji Shobanke, Mehul Bhatt, Ekundayo Shittu
Advances in Applied Energy (2025), pp. 100211-100211
Open Access | Times Cited: 4
An Overview of Multi-Agent Reinforcement Learning from Game Theoretical Perspective
Yaodong Yang, Jun Wang
arXiv (Cornell University) (2020)
Open Access | Times Cited: 123
Reinforcement Learning Techniques for Optimal Power Control in Grid-Connected Microgrids: A Comprehensive Review
Erick O. Arwa, Komla A. Folly
IEEE Access (2020) Vol. 8, pp. 208992-209007
Open Access | Times Cited: 98
Hierarchical Deep Reinforcement Learning for Backscattering Data Collection With Multiple UAVs
Yu Zhang, Zhiyu Mou, Feifei Gao, et al.
IEEE Internet of Things Journal (2020) Vol. 8, Iss. 5, pp. 3786-3800
Open Access | Times Cited: 95
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