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.
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页码：1013 / 1020
页数：8
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