Value Function Estimation

Value Function Estimation is a computational method in preference modeling that quantifies the relative desirability of alternatives by assigning scalar values to outcomes based on observed preferences, thereby enabling the prediction and optimization of decision-making behavior.

566

Publications

45.4K

Citations

1.2K

Authors

501

Institutions

Publications per year

2017–2026

158

Authors

1.2K

  1. SM
    Shie Mannor

    Technion – Israel Institute of Technology, Israel

    10 publications · 795 citations

    10

    h-index

  2. DS
    David Silver

    Google DeepMind (United Kingdom), United Kingdom

    7 publications · 6K citations

    7

    h-index

  3. DP
    Doina Precup

    McGill University, Canada

    6 publications · 137 citations

    6

    h-index

  4. OP
    Olivier Pietquin

    Supélec, France

    6 publications · 180 citations

    6

    h-index

  5. MG
    Mohammad Ghavamzadeh

    Adobe Systems (United States), United States

    7 publications · 274 citations

    6

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 51 publications · 9.4K citations

    27

    h-index

  2. SIAM Journal on Control and Optimization

    14 publications · 595 citations

    14

    h-index

  3. Management Science

    11 publications · 1.7K citations

    11

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 12 publications · 772 citations

    10

    h-index

  5. IEEE Transactions on Automatic Control

    8 publications · 1K citations

    8

    h-index

1–5