Multiagent Pomdps

Multiagent POMDPs is a decentralized stochastic planning framework that extends the partially observable Markov decision process to multiagent settings by modeling cooperative decision-making under uncertainty, where multiple agents maintain individual beliefs and act based on local observations while sharing a common goal.

179

Publications

9.5K

Citations

313

Authors

141

Institutions

Publications per year

2017–2026

43

Authors

313

  1. MT
    Matthijs T. J. Spaan

    Delft University of Technology, Netherlands

    17 publications · 650 citations

    17

    h-index

  2. SZ
    Shlomo Zilberstein

    University of Massachusetts Amherst, United States

    18 publications · 1K citations

    16

    h-index

  3. CA
    Christopher Amato

    Massachusetts Institute of Technology, United States

    17 publications · 915 citations

    16

    h-index

  4. FA
    Frans A. Oliehoek

    University of Amsterdam, Netherlands

    15 publications · 468 citations

    13

    h-index

  5. MT
    Milind Tambe

    University of Southern California, United States

    12 publications · 968 citations

    12

    h-index

1–5 of 313

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 715 citations

    9

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 350 citations

    9

    h-index

  3. Journal of Artificial Intelligence Research

    JAIR · 8 publications · 695 citations

    8

    h-index

  4. 6

    h-index

  5. IEEE Internet of Things Journal

    5 publications · 386 citations

    5

    h-index

1–5