Probabilistic Action Representation
Probabilistic Action Representation is a formal framework in cognitive science and artificial intelligence that models actions as probability distributions over possible outcomes, incorporating uncertainty in action selection and execution within dynamic environments.
112
Publications
7K
Citations
297
Authors
130
Institutions
Publications per year
2017–2026
24
Parents
112
1–5 of 112
297
4
h-index
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 297
130
Carnegie Mellon University
Pittsburgh, United States
6 h-index
8 publications
686 citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
9 publications
584 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
11 publications
781 citations
Technical University of Munich
Munich, Germany
4 h-index
9 publications
372 citations
Technische Universität Berlin
Berlin, Germany
4 h-index
7 publications
1.3K citations

University of Rochester
Rochester, United States
4 h-index
13 publications
1.4K citations
University of Washington
Seattle, United States
4 h-index
10 publications
1.2K citations
The University of Texas at Austin
Austin, United States
3 h-index
6 publications
390 citations
1–8 of 130
Repository · 7 publications · 192 citations
7
h-index
Conference · 4 publications · 359 citations
4
h-index
JAIR · 4 publications · 332 citations
4
h-index
2 publications · 60 citations
2
h-index
Conference · 2 publications · 103 citations
2
h-index
1–5