Shapley Operator

The **Shapley Operator** is a mathematical operator in stochastic game theory that maps value functions to value functions by combining expected payoffs and optimal transition choices, distinguished by its role in characterizing the dynamic programming recursion for zero-sum stochastic games with discounted or average payoffs.

393

Publications

41.4K

Citations

1.1K

Authors

533

Institutions

Publications per year

2017–2026

276

Authors

1.1K

  1. FM
    Fanyong Meng

    Central South University, China

    9 publications · 429 citations

    9

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  2. RB
    R. Brânzei

    Alexandru Ioan Cuza University, Romania

    4 publications · 165 citations

    4

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  3. ST
    S.H. Tijs

    Tilburg University, Netherlands

    4 publications · 165 citations

    4

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  4. JM
    J. M. Alonso-Meijide

    Universidade de Santiago de Compostela, Spain

    4 publications · 63 citations

    4

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  5. SZ
    Sırma Zeynep Alparslan Gök

    Süleyman Demirel University, Türkiye

    4 publications · 165 citations

    4

    h-index

1–5 of 1.1K

Venues

  1. Games and Economic Behavior

    10 publications · 460 citations

    10

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  2. arXiv (Cornell University)

    Repository · 11 publications · 8K citations

    10

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  3. International Journal of Game Theory

    8 publications · 676 citations

    8

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  4. European Journal of Operational Research

    7 publications · 464 citations

    7

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  5. Expert Systems with Applications

    3 publications · 117 citations

    6

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1–5