Demonstration Generalization
Demonstration Generalization is a formal methodological framework within Learning from Demonstration that enables the extension of task-specific policies derived from a limited set of human demonstrations to broader, unseen task instances by inferring invariant features and structural regularities across demonstration examples.
38
Publications
2.5K
Citations
113
Authors
40
Institutions
Publications per year
2017–2026
13
Parents
38
Your wish is my command: programming by example
Choice Reviews Online · 2001 · 500 citations
Natural methods for robot task learning
Monica Nicolescu, Maja J. Matarić · 2003 · 344 citations
Toby Jia-Jun Li, Amos Azaria, Brad A. Myers · 2017 · 187 citations
Learning and generalization of complex tasks from unstructured demonstrations
Scott Niekum, Sarah Osentoski, George Konidaris et al. · 2012 · 174 citations
1–5 of 38
113
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 113
40
Carnegie Mellon University
Pittsburgh, United States
6 h-index
11 publications
812 citations

Italian Institute of Technology
Genoa, Italy
2 h-index
7 publications
331 citations
University of Washington
Seattle, United States
2 h-index
6 publications
208 citations
University of Southern California
Los Angeles, United States
2 h-index
4 publications
744 citations

University of Massachusetts Amherst
Amherst Center, United States
2 h-index
4 publications
734 citations
Robert Bosch (United States)
Farmington Hills, United States
2 h-index
2 publications
367 citations

Technische Universität Darmstadt
Darmstadt, Germany
2 h-index
8 publications
369 citations
University of Hertfordshire
Hatfield, United Kingdom
1 h-index
4 publications
100 citations
1–8 of 40
Repository · 4 publications · 74 citations
4
h-index
2 publications · 47 citations
2
h-index
JR · 1 publications · 20 citations
1
h-index
1 publications · 11 citations
1
h-index
IJRR · 1 publications · 193 citations
1
h-index
1–5