Human-computer Co-performance

Human-Computer Co-Performance is a performative framework in which human and computational agents dynamically and reciprocally generate artistic output in real time, distinguished from other performance models by its emphasis on mutual responsiveness, shared agency, and improvisational interdependence between the human and algorithmic processes within live coding and generative performance contexts.

28

Publications

1.3K

Citations

85

Authors

33

Institutions

Publications per year

2017–2026

11

Authors

85

  1. VP
    Viraj Prabhu

    Georgia Institute of Technology, United States

    2 publications · 73 citations

    2

    h-index

  2. SL
    Stefan Lee

    Georgia Institute of Technology, United States

    2 publications · 73 citations

    2

    h-index

  3. AC
    Arjun Chandrasekaran

    Georgia Institute of Technology, United States

    2 publications · 73 citations

    2

    h-index

  4. DP
    Devi Parikh

    Georgia Institute of Technology, United States

    2 publications · 73 citations

    2

    h-index

  5. AD
    Abhishek Das

    Georgia Institute of Technology, United States

    2 publications · 73 citations

    2

    h-index

1–5 of 85

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 59 citations

    2

    h-index

  2. AI & Society

    1 publications · 29 citations

    1

    h-index

  3. 1

    h-index

  4. Experimental Brain Research

    1 publications · 103 citations

    1

    h-index

  5. Creativity Research Journal

    1 publications · 178 citations

    1

    h-index

1–5