Distributional Value Functions

Distributional Value Function is a value function in reinforcement learning that models the entire probability distribution of cumulative rewards, rather than only their expected value, thereby capturing the inherent stochasticity in returns.

43

Publications

2.7K

Citations

85

Authors

65

Institutions

Publications per year

2017–2026

13

Authors

85

  1. RM
    Rémi Munos

    Google (United States), United States

    6 publications · 1.4K citations

    6

    h-index

  2. WD
    Will Dabney

    Google (United States), United States

    6 publications · 1.4K citations

    6

    h-index

  3. MG
    Marc G. Bellemare

    Google (United States), United States

    5 publications · 958 citations

    5

    h-index

  4. MR
    Mark Rowland

    Google (United States), United States

    4 publications · 717 citations

    4

    h-index

  5. AG
    Arthur Gretton

    University College London, United Kingdom

    2 publications · 37 citations

    2

    h-index

1–5 of 85

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 472 citations

    5

    h-index

  2. Economica

    2 publications · 84 citations

    2

    h-index

  3. Dynamic Games and Applications

    1 publications · 10 citations

    1

    h-index

  4. Monatshefte für Mathematik

    1 publications · 25 citations

    1

    h-index

  5. Journal of the London Mathematical Society

    1 publications · 26 citations

    1

    h-index

1–5