Causal Action Models

Causal Action Models is a computational framework within action representation that formally encodes the causal relationships between actions, their preconditions, and effects, distinguishing itself from associative or statistical action models by explicitly modeling intervention outcomes and counterfactual dependencies in dynamic environments.

68

Publications

3.8K

Citations

153

Authors

112

Institutions

Publications per year

2017–2026

24

Authors

153

  1. AG
    Alison Gopnik

    University of California, Berkeley, United States

    3 publications · 455 citations

    3

    h-index

  2. JP
    J. P. Vigier

    Institut Henri Poincaré, France

    2 publications · 46 citations

    2

    h-index

  3. DA
    Dare A. Baldwin

    University of Oregon, United States

    2 publications · 103 citations

    2

    h-index

  4. SJ
    Samuel J. Gershman

    Harvard University, United States

    2 publications · 192 citations

    2

    h-index

  5. SA
    Susan A. Gelman

    University of Michigan, United States

    2 publications · 202 citations

    2

    h-index

1–5 of 153

Venues

  1. Child Development

    3 publications · 231 citations

    3

    h-index

  2. Developmental Science

    3 publications · 303 citations

    3

    h-index

  3. National Conference on Artificial Intelligence

    Conference · 2 publications · 43 citations

    2

    h-index

  4. Cognition

    2 publications · 394 citations

    2

    h-index

  5. American Journal of Epidemiology

    AJE · 2 publications · 308 citations

    2

    h-index

1–5