Robust Multi-agent Learning
Robust Multi-Agent Learning is a multi-agent learning framework that ensures consistent performance and convergence under environmental uncertainties, adversarial disturbances, and partial observability by explicitly incorporating resilience mechanisms into agents' decision-making processes.
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2.9K
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122
Authors
58
Institutions
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2017–2026
31
Parents
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Nirmal Marwah, Vivek Kumar Singh, Gautam Siddharth Kashyap et al. · International Journal of Information Technology · 2023 · 128 citations · Full text
Engineering, Agricultural Engineering, Autonomous Systems +14
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University of California, Berkeley
Berkeley, United States
3 h-index
4 publications
670 citations
Vector Institute
Toronto, Canada
2 h-index
2 publications
70 citations
Northeastern University
Boston, United States
2 h-index
2 publications
209 citations

Zhejiang University
Hangzhou, China
2 h-index
3 publications
111 citations
Tongji University
Shanghai, China
2 h-index
7 publications
306 citations

Harvard University Press
Cambridge, United States
2 h-index
2 publications
70 citations
Virginia Tech
Blacksburg, United States
2 h-index
2 publications
94 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
5 publications
678 citations
1–8 of 58
Repository · 9 publications · 1.3K citations
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ITIVBL · 2 publications · 56 citations
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2 publications · 62 citations
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1 publications · 47 citations
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Conference · 1 publications · 10 citations
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