Long-run Average Cost

Long-Run Average Cost is a performance metric in Infinite-Horizon Markov Decision Processes that quantifies the expected average cost per time step accumulated over an infinite time horizon, distinguishing itself from discounted-cost criteria by focusing on sustained asymptotic behavior rather than time-discounted rewards.

396

Publications

19.5K

Citations

646

Authors

369

Institutions

Publications per year

2017–2026

48

Variants

Average Cost CriterionLong-run Average Cost Criterion

Authors

646

  1. AF
    Awi Federgruen

    Columbia University, United States

    9 publications · 831 citations

    9

    h-index

  2. YL
    Yuan Lin Zhang

    Southeast University, China

    9 publications · 387 citations

    9

    h-index

  3. DZ
    Dror Zuckerman

    Hebrew University of Jerusalem, Israel

    8 publications · 221 citations

    8

    h-index

  4. VM
    Viliam Makiš

    University of Toronto, Canada

    7 publications · 420 citations

    7

    h-index

  5. SW
    Singa Wang Chiu

    Chaoyang University of Technology, Taiwan

    7 publications · 115 citations

    7

    h-index

1–5 of 646

Venues

  1. Operations Research

    36 publications · 2.2K citations

    25

    h-index

  2. Journal of Applied Probability

    JAP · 36 publications · 1.2K citations

    22

    h-index

  3. IEEE Transactions on Automatic Control

    23 publications · 1.3K citations

    20

    h-index

  4. Management Science

    20 publications · 2.4K citations

    20

    h-index

  5. IEEE Transactions on Reliability

    15 publications · 686 citations

    15

    h-index

1–5