Horizontal gene transfer for recombining graphs

We introduce a form of neutral horizontal gene transfer (HGT) to evolving graphs by graph programming (EGGP). We introduce the μ × λ evolutionary algorithm (EA), where μ parents each produce λ children who compete only with their parents. HGT events then copy the entire active component of one survi...

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Veröffentlicht in:	Genetic programming and evolvable machines Jg. 21; H. 3; S. 321 - 347
Hauptverfasser:	Atkinson, Timothy, Plump, Detlef, Stepney, Susan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Biomedical Engineering and Bioengineering Cartesian coordinates Children Compilers Computer Science Electrical Engineering Evolutionary algorithms Genetic algorithms Graphs Interpreters Parents Performance enhancement Programming Programming Languages Programming Techniques Software Engineering/Programming and Operating Systems Special Issue: Highlights of Genetic Programming 2019 Events Neuroevolution Graph-based genetic programming Horizontal gene transfer
ISSN:	1389-2576, 1573-7632
Online-Zugang:	Volltext
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