Learning Under Uncertainty

Learning Under Uncertainty is a theoretical framework in the study of learning in experiments that characterizes how agents acquire and update knowledge in dynamic environments where outcomes are probabilistic, feedback is incomplete, or the underlying model of the world is not fully known.

655

Publications

50.4K

Citations

1.4K

Authors

634

Institutions

Publications per year

2017–2026

179

Authors

1.4K

  1. WK
    W. K. Estes

    Rockefeller University, United States

    6 publications · 882 citations

    6

    h-index

  2. AJ
    Ali Jadbabaie

    University of Pennsylvania, United States

    6 publications · 271 citations

    6

    h-index

  3. PD
    Peter Dayan

    University College London, United Kingdom

    6 publications · 704 citations

    6

    h-index

  4. ND
    Nathaniel D. Daw

    Princeton University, United States

    6 publications · 454 citations

    6

    h-index

  5. PS
    Philipp Strack

    Yale University, United States

    6 publications · 311 citations

    6

    h-index

1–5 of 1.4K

Venues

  1. arXiv (Cornell University)

    Repository · 36 publications · 3.5K citations

    26

    h-index

  2. SSRN Electronic Journal

    Repository · 23 publications · 685 citations

    16

    h-index

  3. Journal of Economic Dynamics and Control

    13 publications · 844 citations

    13

    h-index

  4. Journal of Experimental Psychology

    15 publications · 575 citations

    12

    h-index

  5. Psychological Review

    11 publications · 1.1K citations

    11

    h-index

1–5