Human-robot Trust Models
Human-Robot Trust Models is a theoretical or computational framework that specifies the formation, evolution, and influence of trust in interactions between humans and robots, distinguishing itself from other trust models by explicitly accounting for the bidirectional, context-dependent, and often asymmetric dynamics unique to human-robot relationships.
294
Publications
17.3K
Citations
684
Authors
274
Institutions
Publications per year
2017–2026
214
294
1–5 of 294
684
12
h-index
10
h-index
9
h-index
United States Air Force Research Laboratory, United States
8 publications · 446 citations
9
h-index
8
h-index
1–5 of 684
274
Georgia Institute of Technology
Atlanta, United States
15 h-index
45 publications
2.6K citations

University of Central Florida
Orlando, United States
13 h-index
47 publications
3.2K citations
University of Michigan
Ann Arbor, United States
13 h-index
25 publications
1.2K citations
Carnegie Mellon University
Pittsburgh, United States
12 h-index
20 publications
1.5K citations
Clemson University
Clemson, United States
11 h-index
37 publications
1.6K citations
University of Massachusetts Lowell
Lowell, United States
11 h-index
24 publications
1.7K citations

United States Air Force Research Laboratory
Wright-Patterson AFB, United States
10 h-index
16 publications
604 citations
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
21 publications
1.5K citations
1–8 of 274
19 publications · 1.8K citations
19
h-index
10 publications · 500 citations
11
h-index
7 publications · 361 citations
7
h-index
6 publications · 241 citations
7
h-index
5 publications · 177 citations
6
h-index
1–5