Discounted Reward Optimization

Discounted Reward Optimization is a sequential decision-making framework in Markov Decision Processes that belongs to the class of objective criteria for evaluating policies, distinguished by its maximization of the expected sum of discounted rewards over time, where future rewards are attenuated by a discount factor less than one.

142

Publications

7.3K

Citations

336

Authors

193

Institutions

Publications per year

2017–2026

39

Authors

336

  1. ML
    Mingyan Liu

    University of Michigan, United States

    4 publications · 512 citations

    4

    h-index

  2. SH
    Sahand Haji Ali Ahmad

    University of Michigan, United States

    4 publications · 512 citations

    4

    h-index

  3. MA
    Mohamed Abd Allah El‐Hadidy

    Tanta University, Egypt

    3 publications · 60 citations

    3

    h-index

  4. SZ
    Shaohui Zheng

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 49 citations

    2

    h-index

  5. CB
    C. Buyukkoc

    University of California, Berkeley, United States

    2 publications · 325 citations

    2

    h-index

1–5 of 336

Venues

  1. IEEE Transactions on Automatic Control

    5 publications · 529 citations

    5

    h-index

  2. International Journal of Production Economics

    5 publications · 179 citations

    5

    h-index

  3. European Journal of Operational Research

    5 publications · 323 citations

    5

    h-index

  4. Operations Research

    5 publications · 161 citations

    5

    h-index

  5. Journal of Applied Probability

    JAP · 3 publications · 87 citations

    3

    h-index

1–5