Surrogate-assisted Interactive Evolution

Surrogate-Assisted Interactive Evolution is an evolutionary optimization framework that incorporates surrogate models to approximate human fitness evaluations, thereby reducing the cognitive burden on human evaluators during interactive evolutionary processes.

2

Publications

47

Citations

13

Authors

10

Institutions

Publications per year

2017–2026

0

Authors

13

  1. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    1 publications · 24 citations

    1

    h-index

  2. JL
    Jacques Lévy Véhel

    Institut national de recherche en sciences et technologies du numérique, France

    1 publications · 23 citations

    1

    h-index

  3. ÉL
    Évelyne Lutton

    Institut national de recherche en sciences et technologies du numérique, France

    1 publications · 23 citations

    1

    h-index

  4. XL
    Xavier Llorà

    University of Illinois Urbana-Champaign, United States

    1 publications · 24 citations

    1

    h-index

  5. KS
    Kumara Sastry

    University of Illinois Urbana-Champaign, United States

    1 publications · 24 citations

    1

    h-index

1–5 of 13

Venues

  1. Genetic Programming and Evolvable Machines

    1 publications · 23 citations

    1

    h-index

  2. Applied Soft Computing

    1 publications · 14 citations

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