The Univariate Marginal Distribution Algorithm Copes Well with Deception and Epistasis

In their recent work, Lehre and Nguyen (2019) show that the univariate marginal distribution algorithm (UMDA) needs time exponential in the parent populations size to optimize the DeceptiveLeadingBlocks (DLB) problem. They conclude from this result that univariate EDAs have difficulties with decepti...

Celý popis

Podrobná bibliografia

Vydané v:	Evolutionary computation Ročník 29; číslo 4; s. 543
Hlavní autori:	Doerr, Benjamin, Krejca, Martin S
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.12.2021
Predmet:	Algorithms Biological Evolution Epistasis, Genetic Models, Genetic Population Density Estimation-of-distribution algorithm runtime analysis univariate marginal distribution algorithm epistasis theory
ISSN:	1530-9304, 1530-9304
On-line prístup:	Zistit podrobnosti o prístupe
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!