A Relaxed Approach to Simplification in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Johnston:2010:EuroGP,

• author = "Mark Johnston and Thomas Liddle and Mengjie Zhang",
• title = "A Relaxed Approach to Simplification in Genetic Programming",
• booktitle = "Proceedings of the 13th European Conference on Genetic Programming, EuroGP 2010",
• year = "2010",
• editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and Sara Silva and Stephen Dignum and A. Sima Uyar",
• volume = "6021",
• series = "LNCS",
• pages = "110--121",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-12147-0",
• DOI = "doi:10.1007/978-3-642-12148-7_10",
• abstract = "We propose a novel approach to program simplification in tree-based Genetic Programming, based upon numerical relaxations of algebraic rules. We also separate proposal of simplifications from an acceptance criterion that checks the effect of proposed simplifications on the evaluation of training examples, looking several levels up the tree. We test our simplification method on three classification datasets and conclude that the success of linear regression is dataset dependent, that looking further up the tree can catch ineffective simplifications, and that CPU time can be significantly reduced while maintaining classification accuracy on unseen examples.",
• notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010 held in conjunction with EvoCOP2010 EvoBIO2010 and EvoApplications2010",

}

Genetic Programming entries for Mark Johnston Thomas Liddle Mengjie Zhang

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