Skill Abstraction
Skill Abstraction is a methodological construct in self-supervised robot learning that identifies and encapsulates low-level sensorimotor patterns into reusable, high-level behavioral units to enable efficient generalization and transfer across tasks.
45
Publications
2.3K
Citations
138
Authors
50
Institutions
Publications per year
2017–2026
22
45
1–5 of 45
138
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University of Massachusetts Amherst
Amherst Center, United States
6 h-index
13 publications
1.1K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
9 publications
201 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
4 publications
128 citations
Google (United States)
Mountain View, United States
2 h-index
6 publications
344 citations
Institute of Cognitive Sciences and Technologies
Rome, Italy
2 h-index
4 publications
272 citations

Indian Institute of Technology Madras
Chennai, India
2 h-index
2 publications
47 citations

University of Freiburg
Freiburg im Breisgau, Germany
1 h-index
2 publications
132 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
1 h-index
3 publications
45 citations
1–8 of 50
Repository · 11 publications · 841 citations
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TAMD · 2 publications · 116 citations
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2 publications · 86 citations
2
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Repository · 1 publications · 78 citations
1
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1 publications · 89 citations
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