Stochastic Bayesian Games

Stochastic Bayesian Games is a formal game-theoretic framework that extends Bayesian games by incorporating stochastic state transitions, where players jointly influence the evolution of a dynamic environment with imperfect information about others' types and the underlying state.

16

Publications

1.5K

Citations

35

Authors

19

Institutions

Publications per year

2017–2026

5

Authors

35

  1. MS
    Michael Shum

    John Brown University, United States

    2 publications · 69 citations

    2

    h-index

  2. ML
    Michael L. Littman

    Rutgers, The State University of New Jersey, United States

    2 publications · 69 citations

    2

    h-index

  3. LS
    Lones Smith

    University of Wisconsin–Madison, United States

    2 publications · 845 citations

    2

    h-index

  4. MK
    Max Kleiman‐Weiner

    Massachusetts Institute of Technology, United States

    2 publications · 69 citations

    2

    h-index

  5. JB
    Joshua B. Tenenbaum

    Massachusetts Institute of Technology, United States

    2 publications · 69 citations

    2

    h-index

1–5 of 35

Venues

  1. International Journal of Game Theory

    2 publications · 136 citations

    2

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  2. arXiv (Cornell University)

    Repository · 2 publications · 90 citations

    2

    h-index

  3. Econometrica

    2 publications · 894 citations

    2

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5