Model-based Reasoning

Model-Based Reasoning is a formal reasoning paradigm in expert systems that relies on an explicit, computational representation of the principles governing a physical or conceptual system to generate and justify inferences through simulation and abductive or diagnostic analysis, distinguishing it from heuristic or data-driven reasoning by its foundation in structural and behavioral models.

624

Publications

32.6K

Citations

1.5K

Authors

572

Institutions

Publications per year

2017–2026

100

Variants

Mbr

Authors

1.5K

  1. PN
    P. N. Johnson‐Laird

    Princeton University, United States

    8 publications · 741 citations

    8

    h-index

  2. JT
    Jan Treur

    Vrije Universiteit Amsterdam, Netherlands

    7 publications · 158 citations

    7

    h-index

  3. YI
    Yumi Iwasaki

    Stanford University, United States

    5 publications · 157 citations

    5

    h-index

  4. FW
    Franz Wotawa

    Graz University of Technology, Austria

    5 publications · 122 citations

    5

    h-index

  5. RM
    Ruth M. J. Byrne

    Trinity College Dublin, Ireland

    5 publications · 458 citations

    5

    h-index

1–5 of 1.5K

Venues

  1. Artificial Intelligence

    14 publications · 1.2K citations

    14

    h-index

  2. arXiv (Cornell University)

    Repository · 10 publications · 487 citations

    10

    h-index

  3. Expert Systems with Applications

    9 publications · 286 citations

    9

    h-index

  4. Decision Support Systems

    8 publications · 350 citations

    8

    h-index

  5. PubMed

    Repository · 8 publications · 302 citations

    8

    h-index

1–5