Real-time Decision Making

Real-Time Decision Making is a computational framework within improvisational choreography and autonomous movement systems that enables an agent to dynamically select and adjust actions during performance or interaction based on immediate sensory feedback and environmental contingencies, distinguishing it from pre-scripted or predictive decision models by its reliance on continuous, low-latency processing of unfolding kinesthetic and spatial data.

473

Publications

21.4K

Citations

1.8K

Authors

704

Institutions

Publications per year

2017–2026

223

Authors

1.8K

  1. HA
    Howard A. Schwid

    University of Washington, United States

    4 publications · 219 citations

    4

    h-index

  2. HX
    Hui Xiong

    Rutgers, The State University of New Jersey, United States

    4 publications · 170 citations

    4

    h-index

  3. GN
    Gene N. Peterson

    University of Washington, United States

    4 publications · 219 citations

    4

    h-index

  4. BG
    Bala G. Nair

    University of Washington, United States

    4 publications · 219 citations

    4

    h-index

  5. AS
    Adam Stotz

    University at Buffalo, State University of New York, United States

    3 publications · 101 citations

    3

    h-index

1–5 of 1.8K

Venues

  1. 8

    h-index

  2. arXiv (Cornell University)

    Repository · 7 publications · 143 citations

    7

    h-index

  3. IEEE Transactions on Smart Grid

    4 publications · 108 citations

    4

    h-index

  4. Sensors

    4 publications · 261 citations

    4

    h-index

  5. Procedia CIRP

    4 publications · 154 citations

    4

    h-index

1–5