Multi-armed Bandit Experiments

Multi-Armed Bandit Experiments is a sequential experimentation strategy that, as a type of adaptive experimental design, dynamically allocates treatment assignments to optimize cumulative rewards by balancing exploration and exploitation across competing intervention arms.

114

Publications

8.2K

Citations

268

Authors

151

Institutions

Publications per year

2017–2026

65

Variants

MabMulti-armed Bandit

Authors

268

  1. ES
    Eric Schulz

    University College London, United Kingdom

    13 publications · 946 citations

    12

    h-index

  2. MS
    Maarten Speekenbrink

    University College London, United Kingdom

    8 publications · 295 citations

    8

    h-index

  3. AR
    Aaditya Ramdas

    Carnegie Mellon University, United States

    5 publications · 140 citations

    5

    h-index

  4. GK
    Godfrey Keller

    University of Oxford, United Kingdom

    5 publications · 682 citations

    5

    h-index

  5. CM
    Charley M. Wu

    Max Planck Institute for Human Development, Germany

    5 publications · 215 citations

    5

    h-index

1–5 of 268

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 416 citations

    10

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 8 publications · 163 citations

    7

    h-index

  3. SSRN Electronic Journal

    Repository · 5 publications · 149 citations

    5

    h-index

  4. PLoS Computational Biology

    4 publications · 197 citations

    4

    h-index

  5. Econometrica

    4 publications · 929 citations

    4

    h-index

1–5