VGN: Value Decomposition With Graph Attention Networks for Multiagent Reinforcement Learning

Author:

Wei Qinglai1ORCID,Li Yugu2,Zhang Jie2ORCID,Wang Fei-Yue3ORCID

Affiliation:

1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China, also with the School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China, and also with the Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China.

2. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

3. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China, also with the Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China, and also with the Qingdao Academy of Intelligent Industries, Qingdao 266109, China.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

National Defense Basic Scientific Research Program

Science and Technology Development Fund Macau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. VHGN: Cooperative Multiagent Reinforcement Learning with Historical Information Graph;2023 IEEE International Conference on Big Data (BigData);2023-12-15

2. Abbreviated Weighted Graph in Multi-Agent Reinforcement Learning;PRICAI 2023: Trends in Artificial Intelligence;2023-11-10

3. Research on Risk Assessment Model for Social High-Risk Individuals Based on Graph Attention Network;2023 IEEE 10th International Conference on Cyber Security and Cloud Computing (CSCloud)/2023 IEEE 9th International Conference on Edge Computing and Scalable Cloud (EdgeCom);2023-07

4. BRGR: Multi-agent cooperative reinforcement learning with bidirectional real-time gain representation;Applied Intelligence;2023-02-17

5. Constrained-Cost Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems;IEEE Transactions on Neural Networks and Learning Systems;2023

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