Multi-agent Curriculum Learning
Multi-Agent Curriculum Learning is a structured learning framework in which the training of multiple interacting agents is progressively organized through a sequence of tasks or environments of increasing complexity to facilitate coordinated skill acquisition and convergence in multi-agent systems.
27
Publications
1.2K
Citations
93
Authors
33
Institutions
Publications per year
2017–2026
25
Parents
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Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov et al. · arXiv (Cornell University) · 2017 · 142 citations · Full text
1–5 of 27
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Institut national de recherche en sciences et technologies du numérique, France
2 publications · 67 citations
2
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1–5 of 93
33
The University of Texas at Austin
Austin, United States
3 h-index
9 publications
644 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
2 publications
70 citations
Meta (Israel)
Tel Aviv, Israel
2 h-index
7 publications
746 citations

University of Applied Sciences and Arts of Southern Switzerland
Manno, Switzerland
2 h-index
2 publications
222 citations
Shandong University of Political Science and Law
Jinan, China
2 h-index
2 publications
222 citations
Institut Systèmes Intelligents et de Robotique
Paris, France
2 h-index
5 publications
176 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
128 citations
OpenAI (United States)
San Francisco, United States
2 h-index
2 publications
55 citations
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Repository · 6 publications · 280 citations
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Conference · 2 publications · 136 citations
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1 publications · 180 citations
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Conference · 1 publications · 80 citations
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1 publications · 35 citations
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