Distributed Multi-robot Learning

Distributed Multi-Robot Learning is a decentralized machine learning framework in which multiple robotic agents independently acquire and share knowledge through local interactions and coordinated learning protocols without relying on a centralized coordinator or global information access.

24

Publications

1K

Citations

63

Authors

31

Institutions

Publications per year

2017–2026

10

Variants

Decentralized Multi-robot Learning

Authors

63

  1. AM
    Alcherio Martinoli

    École Polytechnique Fédérale de Lausanne, Switzerland

    5 publications · 227 citations

    5

    h-index

  2. MJ
    Maja J. Matarić

    University of Southern California, United States

    2 publications · 36 citations

    2

    h-index

  3. ED
    Ezequiel Di Mario

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 24 citations

    2

    h-index

  4. JP
    Jim Pugh

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 149 citations

    2

    h-index

  5. HM
    Hung Manh La

    University of Nevada, Reno, United States

    2 publications · 214 citations

    2

    h-index

1–5 of 63

Venues

  1. IEEE Robotics and Automation Letters

    2 publications · 115 citations

    2

    h-index

  2. Swarm Intelligence

    1 publications · 36 citations

    1

    h-index

  3. PLoS ONE

    1 publications · 22 citations

    1

    h-index

  4. The International Journal of Robotics Research

    IJRR · 1 publications · 31 citations

    1

    h-index

  5. Journal of Intelligent & Robotic Systems

    1 publications · 31 citations

    1

    h-index

1–5