Decentralized Pomdps

Decentralized POMDPs is a multi-agent decision-theoretic framework that extends the Partially Observable Markov Decision Process by modeling cooperative decision-making under uncertainty in systems where multiple agents operate with decentralized information and independently select actions based on their local observations.

101

Publications

5K

Citations

168

Authors

101

Institutions

Publications per year

2017–2026

18

Variants

Decentralized Partially Observable Markov Decision Processes

Authors

168

  1. SZ
    Shlomo Zilberstein

    University of Massachusetts Amherst, United States

    23 publications · 1.2K citations

    19

    h-index

  2. CA
    Christopher Amato

    Massachusetts Institute of Technology, United States

    23 publications · 1.1K citations

    17

    h-index

  3. JP
    Jonathan P. How

    Massachusetts Institute of Technology, United States

    9 publications · 347 citations

    9

    h-index

  4. MT
    Matthijs T. J. Spaan

    Delft University of Technology, Netherlands

    9 publications · 393 citations

    9

    h-index

  5. FA
    Frans A. Oliehoek

    University of Amsterdam, Netherlands

    9 publications · 267 citations

    9

    h-index

1–5 of 168

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 454 citations

    10

    h-index

  2. Journal of Artificial Intelligence Research

    JAIR · 7 publications · 580 citations

    7

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 131 citations

    4

    h-index

  4. UvA-DARE (University of Amsterdam)

    Repository · 3 publications · 64 citations

    3

    h-index

  5. Autonomous Agents and Multi-Agent Systems

    3 publications · 152 citations

    3

    h-index

1–5