Differential Value Function

The **Differential Value Function** is a value function that, within the framework of average reward criteria in Markov decision processes, represents the expected cumulative difference between instantaneous rewards and the long-term average reward, serving to evaluate state-value differences relative to a reference state.

21

Publications

1.9K

Citations

46

Authors

34

Institutions

Publications per year

2017–2026

1

Variants

Relative Value Function

Authors

46

  1. NJ
    N. J. Kalton

    University of Missouri, United States

    2 publications · 66 citations

    2

    h-index

  2. RJ
    Robert J. Elliott

    University of Calgary, Canada

    2 publications · 66 citations

    2

    h-index

  3. JE
    Janice E. Weaver

    University of Kentucky, United States

    1 publications · 64 citations

    1

    h-index

  4. MP
    Martijn Pistorius

    Imperial College London, United Kingdom

    1 publications · 318 citations

    1

    h-index

  5. XY
    Xiaodong Yue

    Capital Normal University, China

    1 publications · 14 citations

    1

    h-index

1–5 of 46

Venues

  1. Journal of Differential Equations

    2 publications · 29 citations

    2

    h-index

  2. Journal of Cognitive Psychology

    1 publications · 91 citations

    1

    h-index

  3. Chinese Journal of Aeronautics

    CJA · 1 publications · 11 citations

    1

    h-index

  4. The Annals of Applied Probability

    1 publications · 318 citations

    1

    h-index

  5. Econometrica

    1 publications · 432 citations

    1

    h-index

1–5