Crossover Bias in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7970

@InProceedings{eurogp07:keijzer,

• author = "Maarten Keijzer and James Foster",
• title = "Crossover Bias in Genetic Programming",
• editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
• booktitle = "Proceedings of the 10th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "4445",
• year = "2007",
• address = "Valencia, Spain",
• month = "11-13 " # apr,
• pages = "33--43",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-71602-5",
• isbn13 = "978-3-540-71602-0",
• DOI = "doi:10.1007/978-3-540-71605-1_4",
• abstract = "Path length, or search complexity, is an under studied phenomenon in genetic programming. Unlike size and depth measures, path length directly measures the balancedness or skewedness of a tree. Here a close relative to path length, called visitation length, is studied. It is shown that a population undergoing standard crossover will introduce a crossover bias in the visitation length. This bias is due to inserting variable length subtrees at various levels of the tree. The crossover bias takes the form of a covariance between the sizes and levels in the trees that form a population. It is conjectured that the crossover bias directly determines the size distribution of trees in genetic programming. Theorems are presented for the one-generation evolution of visitation length both with and without selection. The connection between path length and visitation length is made explicit.",
• notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in conjunction with EvoCOP2007, EvoBIO2007 and EvoWorkshops2007",

}

Genetic Programming entries for Maarten Keijzer James A Foster

Citations