Continuous-time Dynamic Programming

Continuous-Time Dynamic Programming is a mathematical framework within dynamic programming that distinguishes itself by optimizing state trajectories over continuous time intervals using differential equations and Hamilton-Jacobi-Bellman equations, as opposed to discrete time steps.

119

Publications

9.6K

Citations

233

Authors

147

Institutions

Publications per year

2017–2026

22

Authors

233

  1. RB
    Richard Bellman

    RAND Corporation, United States

    7 publications · 418 citations

    7

    h-index

  2. FL
    Frank L. Lewis

    The University of Texas at Arlington, United States

    4 publications · 223 citations

    4

    h-index

  3. DV
    Draguna Vrabie

    Pacific Northwest National Laboratory, United States

    4 publications · 223 citations

    4

    h-index

  4. CW
    Chung-Lie Wang

    University of Regina, Canada

    3 publications · 34 citations

    3

    h-index

  5. RA
    Ronald A. Howard

    Stanford University, United States

    3 publications · 4.3K citations

    3

    h-index

1–5 of 233

Venues

  1. 8

    h-index

  2. Journal of the Operational Research Society

    OR · 5 publications · 705 citations

    5

    h-index

  3. SIAM Journal on Control and Optimization

    5 publications · 163 citations

    5

    h-index

  4. Neurocomputing

    4 publications · 139 citations

    4

    h-index

  5. European Journal of Operational Research

    3 publications · 86 citations

    3

    h-index

1–5