Analysis of Epistasis Correlation on NK Landscapes with Nearest-Neighbor Interactions

被引：0

作者：

Pelikan, Martin ^{[1
]}

机构：

[1] Univ Missouri, Dept Math & Comp Sci, Missouri Estimat Distribut Algorithms Lab, St Louis, MO 63121 USA

来源：

GECCO-2011: PROCEEDINGS OF THE 13TH ANNUAL GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2011年

关键词：

Epistasis; epistasis correlation; problem difficulty; NK landscapes; genetic algorithms; estimation of distribution algorithms; linkage learning; OPTIMIZATION; SCALABILITY;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Epistasis correlation is a measure that estimates the strength of interactions between problem variables. This paper presents an empirical study of epistasis correlation on a large number of random problem instances of NK landscapes with nearest neighbor interactions. The results are analyzed with respect to the performance of hybrid variants of two evolutionary algorithms: (1) the genetic algorithm with uniform crossover and (2) the hierarchical Bayesian optimization algorithm.

引用

页码：1013 / 1020

页数：8

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