Model-based Locomotion Learning
Model-Based Locomotion Learning is a locomotion learning paradigm that belongs to the class of model-based reinforcement learning approaches, distinguished by its reliance on an explicit forward model of the environment dynamics to plan or optimize locomotor policies.
10
Publications
749
Citations
41
Authors
10
Institutions
Publications per year
2017–2026
7
Parents
10
1–5 of 10
41
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 41
10
University of California, Berkeley
Berkeley, United States
3 h-index
9 publications
446 citations
ETH Zurich
Zurich, Switzerland
2 h-index
7 publications
336 citations
Japan Science and Technology Agency
Tokyo, Japan
1 h-index
1 publications
79 citations
University of California, Irvine
Irvine, United States
1 h-index
2 publications
622 citations
Irvine University
Cerritos, United States
1 h-index
2 publications
622 citations
Meta (United States)
Menlo Park, United States
1 h-index
5 publications
210 citations
Harvard University
Cambridge, United States
1 h-index
1 publications
78 citations
Menlo School
Atherton, United States
1 h-index
4 publications
168 citations
1–8 of 10
Repository · 2 publications · 38 citations
2
h-index
2 publications · 88 citations
2
h-index
1 publications · 311 citations
1
h-index
1 publications · 79 citations
1
h-index
PRFluids · 1 publications · 78 citations
1
h-index
1–5