Agent Explainability

Agent Explainability is a methodological framework within intelligent agent research that enables the transparent interpretation of an agent’s decision-making processes by generating human-understandable justifications for its actions, distinguishing it from opaque or black-box agent behaviors.

87

Publications

4.7K

Citations

247

Authors

114

Institutions

Publications per year

2017–2026

64

Authors

247

  1. MB
    Margaret Burnett

    Oregon State University, United States

    6 publications · 514 citations

    6

    h-index

  2. JD
    Jonathan Dodge

    Oregon State University, United States

    5 publications · 147 citations

    5

    h-index

  3. KV
    Karel Van den Bosch

    Utrecht University, Netherlands

    4 publications · 179 citations

    4

    h-index

  4. AW
    A. W. Anderson

    Oregon State University, United States

    4 publications · 133 citations

    4

    h-index

  5. TC
    Tathagata Chakraborti

    Arizona State University, United States

    4 publications · 168 citations

    4

    h-index

1–5 of 247

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 207 citations

    6

    h-index

  2. ACM Transactions on Interactive Intelligent Systems

    TIIS · 3 publications · 102 citations

    3

    h-index

  3. Artificial Intelligence

    3 publications · 180 citations

    3

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 197 citations

    3

    h-index

  5. International Journal of Social Robotics

    2 publications · 73 citations

    2

    h-index

1–5