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

Authors

684

  1. PA
    Peter A. Hancock

    University of Central Florida, United States

    13 publications · 835 citations

    12

    h-index

  2. HA
    Holly A. Yanco

    University of Massachusetts Lowell, United States

    10 publications · 607 citations

    10

    h-index

  3. MD
    Munjal Desai

    University of Massachusetts Lowell, United States

    9 publications · 593 citations

    9

    h-index

  4. JB
    Joseph B. Lyons

    United States Air Force Research Laboratory, United States

    8 publications · 446 citations

    9

    h-index

  5. DR
    Deborah R. Billings

    University of Central Florida, United States

    8 publications · 642 citations

    8

    h-index

1–5 of 684

Venues

  1. International Journal of Social Robotics

    19 publications · 1.8K citations

    19

    h-index

  2. 11

    h-index

  3. Applied Ergonomics

    7 publications · 361 citations

    7

    h-index

  4. IEEE Robotics and Automation Letters

    6 publications · 241 citations

    7

    h-index

  5. Frontiers in Robotics and AI

    5 publications · 177 citations

    6

    h-index

1–5