Stochastic Shortest Path Problems

Stochastic Shortest Path Problems is a type of Markov decision process that involves finding an optimal policy to reach a designated goal state with minimum expected cost in a stochastic environment where transitions and costs are governed by probability distributions.

217

Publications

10K

Citations

457

Authors

246

Institutions

Publications per year

2017–2026

52

Authors

457

  1. DP
    Dimitri P. Bertsekas

    Massachusetts Institute of Technology, United States

    7 publications · 901 citations

    7

    h-index

  2. FT
    Felipe Trevizan

    Australian National University, Australia

    6 publications · 141 citations

    6

    h-index

  3. HG
    Hongliang Guo

    University of Electronic Science and Technology of China, China

    6 publications · 298 citations

    6

    h-index

  4. ZC
    Zhiguang Cao

    Nanyang Technological University, Singapore

    6 publications · 298 citations

    6

    h-index

  5. WH
    William H. K. Lam

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 398 citations

    5

    h-index

1–5 of 457

Venues

  1. Networks

    9 publications · 694 citations

    9

    h-index

  2. European Journal of Operational Research

    6 publications · 191 citations

    6

    h-index

  3. Transportation Research Part B Methodological

    5 publications · 427 citations

    5

    h-index

  4. Mathematics of Operations Research

    5 publications · 573 citations

    5

    h-index

  5. 5

    h-index

1–5