Discount Factor Sensitivity

Discount Factor Sensitivity is a metric in reinforcement learning that quantifies the degree to which an agent's policy or value estimates change in response to variations in the discount factor, distinguishing it from other sensitivity analyses by specifically characterizing the impact of temporal credit assignment on decision-making stability and convergence.

80

Publications

3.9K

Citations

178

Authors

132

Institutions

Publications per year

2017–2026

16

Authors

178

  1. NI
    Nicole Immorlica

    Microsoft (United States), United States

    2 publications · 116 citations

    2

    h-index

  2. MB
    Moshe Babaioff

    Microsoft (United States), United States

    2 publications · 116 citations

    2

    h-index

  3. FR
    Fernando Restoy

    Bank of Spain, Spain

    2 publications · 100 citations

    2

    h-index

  4. AG
    Anupam Gupta

    Carnegie Mellon University, United States

    2 publications · 116 citations

    2

    h-index

  5. MO
    Matthew Osborne

    University of Toronto, Canada

    2 publications · 84 citations

    2

    h-index

1–5 of 178

Venues

  1. Journal of Economic Theory

    JET · 3 publications · 102 citations

    3

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 105 citations

    3

    h-index

  3. National Bureau of Economic Research

    Repository · 3 publications · 368 citations

    3

    h-index

  4. Management Science

    3 publications · 74 citations

    3

    h-index

  5. The RAND Journal of Economics

    3 publications · 438 citations

    3

    h-index

1–5