Continuous-action Pomdps

Continuous-Action POMDPs is a type of partially observable Markov decision process in which the action space is characterized by continuous variables, distinguishing it from discrete-action variants by enabling infinite, real-valued action selections within a bounded or unbounded domain.

20

Publications

2K

Citations

45

Authors

19

Institutions

Publications per year

2017–2026

8

Authors

45

  1. ZN
    Zachary N. Sunberg

    Stanford University, United States

    3 publications · 186 citations

    3

    h-index

  2. MJ
    Mykel J. Kochenderfer

    Stanford University, United States

    3 publications · 186 citations

    3

    h-index

  3. LP
    Leslie Pack Kaelbling

    Massachusetts Institute of Technology, United States

    2 publications · 49 citations

    2

    h-index

  4. KM
    Konstantin M. Seiler

    The University of Sydney, Australia

    1 publications · 74 citations

    1

    h-index

  5. JC
    Jiang Cao

    National University of Defense Technology, China

    1 publications · 16 citations

    1

    h-index

1–5 of 45

Venues

  1. 2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 382 citations

    2

    h-index

  3. DSpace@MIT (Massachusetts Institute of Technology)

    Repository · 1 publications · 39 citations

    1

    h-index

  4. Structure and Infrastructure Engineering

    1 publications · 49 citations

    1

    h-index

  5. Theoretical Computer Science

    1 publications · 71 citations

    1

    h-index

1–5