Abductive Inference

Abductive Inference is a form of logical reasoning that, as a genus of inference distinct from deduction and induction, involves arriving at the most plausible explanation for an observed phenomenon by inferring the best hypothesis that accounts for the available data.

804

Publications

46.1K

Citations

1.5K

Authors

698

Institutions

Publications per year

2017–2026

241

Variants

Inference To The Best Explanation

Authors

1.5K

  1. RA
    R.E. Abdel-Aal

    King Fahd University of Petroleum and Minerals, Saudi Arabia

    13 publications · 567 citations

    13

    h-index

  2. KI
    Katsumi Inoue

    National Institute of Informatics, Japan

    12 publications · 388 citations

    10

    h-index

  3. MD
    Marc Denecker

    KU Leuven, Belgium

    9 publications · 422 citations

    9

    h-index

  4. AR
    Alessandra Russo

    Imperial College London, United Kingdom

    8 publications · 312 citations

    8

    h-index

  5. BD
    Brian D. Haig

    University of Canterbury, New Zealand

    8 publications · 771 citations

    8

    h-index

1–5 of 1.5K

Venues

  1. Logic Journal of IGPL

    19 publications · 586 citations

    15

    h-index

  2. International Joint Conference on Artificial Intelligence

    Conference · 11 publications · 918 citations

    11

    h-index

  3. Semiotica

    9 publications · 335 citations

    9

    h-index

  4. Journal of Logic and Computation

    9 publications · 458 citations

    9

    h-index

  5. Synthese

    9 publications · 334 citations

    9

    h-index

1–5