Learning From Human Demonstration
Learning From Human Demonstration is a subfield of Learning From Demonstration that specifically involves the acquisition of behavioral policies or task knowledge by machines through the observation and interpretation of human-generated action sequences, distinguished by its exclusive focus on human agents as demonstrators rather than synthetic or simulated sources.
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Publications
25.7K
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1.3K
Authors
400
Institutions
Publications per year
2017–2026
200
Variants
Learning From Human Demonstrations
Parents
486
Learning and generalization of motor skills by learning from demonstration
Peter Pástor, H. Hoffmann, Tamim Asfour et al. · 2009 · 710 citations
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang et al. · Nature · 2025 · 568 citations · Full text
Your wish is my command: programming by example
Choice Reviews Online · 2001 · 500 citations
1–5 of 486
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Carnegie Mellon University
Pittsburgh, United States
19 h-index
44 publications
2.3K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
16 h-index
38 publications
6.4K citations
Georgia Institute of Technology
Atlanta, United States
14 h-index
44 publications
3K citations
Massachusetts Institute of Technology
Cambridge, United States
13 h-index
34 publications
2.5K citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
12 h-index
40 publications
2.8K citations
The University of Tokyo
Tokyo, Japan
11 h-index
27 publications
1.1K citations
University of California, Berkeley
Berkeley, United States
11 h-index
39 publications
2.2K citations

Imperial College London
London, United Kingdom
9 h-index
16 publications
515 citations
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Repository · 30 publications · 1.2K citations
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13 publications · 370 citations
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10 publications · 559 citations
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7 publications · 488 citations
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IJRR · 6 publications · 662 citations
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