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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Genetic programming and evolvable machines Ročník 21; číslo 3; s. 321 - 347
Hlavní autoři: Atkinson, Timothy, Plump, Detlef, Stepney, Susan
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2020
Springer Nature B.V
Témata:
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
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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 surviving parent into the inactive component of another parent, exchanging genetic information without reproduction. Experimental results from symbolic regression problems show that the introduction of the μ × λ EA and HGT events improve the performance of EGGP. Comparisons with genetic programming and Cartesian genetic programming strongly favour our proposed approach. We also investigate the effect of using HGT events in neuroevolution tasks. We again find that the introduction of HGT improves the performance of EGGP, demonstrating that HGT is an effective cross-domain mechanism for recombining graphs.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1389-2576
1573-7632
DOI:10.1007/s10710-020-09378-1