Inverse Optimal Control
Inverse Optimal Control is a method in reinforcement learning that infers the underlying reward function from expert demonstrations by identifying the cost criteria that render the observed behavior optimal.
333
Publications
17.7K
Citations
682
Authors
306
Institutions
Publications per year
2017–2026
134
333
Planning-based prediction for pedestrians
Brian D. Ziebart, Nathan Ratliff, Garratt Gallagher et al. · 2009 · 469 citations · Full text
1–5 of 333
682
Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico
27 publications · 730 citations
16
h-index
10
h-index
Universidad Michoacana de San Nicolás de Hidalgo, Mexico
10 publications · 353 citations
10
h-index
8
h-index
8
h-index
1–5 of 682
306

Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional
Mexico City, Mexico
15 h-index
56 publications
1.6K citations

Northeastern University
Shenyang, China
14 h-index
30 publications
3K citations

Universidad de Guadalajara
Guadalajara, Mexico
13 h-index
37 publications
697 citations
Georgia Institute of Technology
Atlanta, United States
10 h-index
19 publications
1.4K citations
University of California San Diego
San Diego, United States
8 h-index
13 publications
3.3K citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
29 publications
5.3K citations
University of Illinois Chicago
Chicago, United States
6 h-index
12 publications
374 citations
Liaoning University of Technology
Jinzhou, China
6 h-index
17 publications
1.9K citations
1–8 of 306
16 publications · 2.9K citations
15
h-index
Repository · 12 publications · 1.1K citations
11
h-index
12 publications · 460 citations
11
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8 publications · 353 citations
8
h-index
8 publications · 356 citations
8
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