Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

Author:

Du Hongyang1ORCID,Zhang Ruichen1ORCID,Liu Yinqiu1ORCID,Wang Jiacheng1ORCID,Lin Yijing2ORCID,Li Zonghang3ORCID,Niyato Dusit1ORCID,Kang Jiawen4ORCID,Xiong Zehui5ORCID,Cui Shuguang6ORCID,Ai Bo7ORCID,Zhou Haibo8ORCID,Kim Dong In9ORCID

Affiliation:

1. College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore

2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, China

3. School of Information and Communication Engineering, University of Electronic Sciences and Technology of China, Chengdu, China

4. School of Automation, Guangdong University of Technology, China

5. Pillar of Information Systems Technology and Design, Singapore University of Technology and Design, Singapore, Singapore

6. School of Science and Engineering (SSE), the Future Network of Intelligence Institute (FNii), and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, The Chinese University of Hong Kong, Shenzhen, China

7. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China

8. School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, China

9. Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea

Funder

IITP

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

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