Automated Algorithm Discovery

Automated Algorithm Discovery is a computational methodology within genetic programming that systematically generates and optimizes algorithms through evolutionary mechanisms, distinguished by its ability to autonomously explore the space of possible algorithmic solutions without human intervention.

39

Publications

5.5K

Citations

109

Authors

51

Institutions

Publications per year

2017–2026

14

Authors

109

  1. QV
    Quoc V. Le

    Google (United States), United States

    3 publications · 302 citations

    3

    h-index

  2. ER
    Esteban Real

    Google (United States), United States

    3 publications · 302 citations

    3

    h-index

  3. JR
    John R. Koza

    Stanford University, United States

    2 publications · 37 citations

    2

    h-index

  4. UO
    Una-May O’Reilly

    Massachusetts Institute of Technology, United States

    2 publications · 553 citations

    2

    h-index

  5. DR
    David R. So

    Google (United States), United States

    2 publications · 135 citations

    2

    h-index

1–5 of 109

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 476 citations

    4

    h-index

  2. cIRcle (University of British Columbia)

    Repository · 2 publications · 200 citations

    2

    h-index

  3. Nature

    2 publications · 613 citations

    2

    h-index

  4. Expert Systems with Applications

    2 publications · 61 citations

    2

    h-index

  5. Artificial Life

    2 publications · 553 citations

    2

    h-index

1–5