Reinforcement Learning For Offloading
Reinforcement Learning for Offloading is a computational framework within task offloading that employs reinforcement learning methods to dynamically optimize offloading decisions by learning optimal policies through agent-environment interactions.
377
Publications
29.6K
Citations
1.3K
Authors
459
Institutions
Publications per year
2017–2026
368
Parents
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459

Beijing University of Posts and Telecommunications
Beijing, China
21 h-index
72 publications
6.6K citations

Xidian University
Xi'an, China
18 h-index
48 publications
3.5K citations

University of Electronic Science and Technology of China
Chengdu, China
17 h-index
29 publications
4.9K citations

Sun Yat-sen University
Guangzhou, China
14 h-index
32 publications
5.7K citations
Queen Mary University of London
London, United Kingdom
12 h-index
31 publications
3.1K citations
Nanyang Technological University
Singapore, Singapore
12 h-index
18 publications
5.3K citations

Zhejiang University
Hangzhou, China
11 h-index
13 publications
2.6K citations

Shanghai Jiao Tong University
Shanghai, China
10 h-index
24 publications
1.1K citations
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41 publications · 3.7K citations
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TMCCI · 15 publications · 2.4K citations
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13 publications · 2.2K citations
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