Decision-theoretic Robot Control

Decision-Theoretic Robot Control is a robotic control framework that uses probabilistic models of actions, states, and outcomes within a utility-based decision-making paradigm to optimize behavior under uncertainty, distinguishing it from reactive or purely geometric approaches by formally integrating beliefs, preferences, and expected utility maximization.

36

Publications

1.2K

Citations

105

Authors

49

Institutions

Publications per year

2017–2026

5

Authors

105

  1. ST
    Sebastian Thrun

    Carnegie Mellon University, United States

    2 publications · 247 citations

    2

    h-index

  2. JP
    Joëlle Pineau

    McGill University, Canada

    2 publications · 108 citations

    2

    h-index

  3. NM
    N.A. Massios

    University of Amsterdam, Netherlands

    2 publications · 20 citations

    2

    h-index

  4. TD
    Taraneh Dean

    University of Portsmouth, United Kingdom

    2 publications · 54 citations

    2

    h-index

  5. JK
    Jak Kirman

    Brown University, United States

    2 publications · 54 citations

    2

    h-index

1–5 of 105

Venues

  1. The International Journal of Robotics Research

    IJRR · 2 publications · 51 citations

    2

    h-index

  2. International Journal of Social Robotics

    2 publications · 110 citations

    2

    h-index

  3. UvA-DARE (University of Amsterdam)

    Repository · 1 publications · 10 citations

    1

    h-index

  4. ACM SIGART Bulletin

    1 publications · 12 citations

    1

    h-index

  5. Applied Ergonomics

    1 publications · 10 citations

    1

    h-index

1–5