Dynamic Genetic Programming

Dynamic Genetic Programming is a variant of genetic programming distinguished by its adaptation of evolutionary parameters, operators, or problem representation during the evolutionary process in response to runtime conditions or performance feedback.

66

Publications

3K

Citations

192

Authors

109

Institutions

Publications per year

2017–2026

21

Authors

192

  1. MZ
    Mengjie Zhang

    Victoria University of Wellington, New Zealand

    5 publications · 263 citations

    5

    h-index

  2. LV
    Leonardo Vanneschi

    Universidade Nova de Lisboa, Portugal

    4 publications · 125 citations

    4

    h-index

  3. HP
    Henri Pierreval

    Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes, France

    2 publications · 60 citations

    2

    h-index

  4. FZ
    Fangfang Zhang

    Victoria University of Wellington, New Zealand

    2 publications · 100 citations

    2

    h-index

  5. NW
    Neal Wagner

    MIT Lincoln Laboratory, United States

    2 publications · 151 citations

    2

    h-index

1–5 of 192

Venues

  1. Expert Systems with Applications

    4 publications · 70 citations

    4

    h-index

  2. Genetic Programming and Evolvable Machines

    4 publications · 156 citations

    4

    h-index

  3. IEEE Transactions on Evolutionary Computation

    4 publications · 286 citations

    4

    h-index

  4. Artificial Life

    2 publications · 553 citations

    2

    h-index

  5. Information Sciences

    2 publications · 45 citations

    2

    h-index

1–5