Analytic Solutions to Differential Equations under Graph-based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@InProceedings{Seaton:2010:EuroGP,

• author = "Tom Seaton and Gavin Brown and Julian Miller",
• title = "Analytic Solutions to Differential Equations under Graph-based 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 = "232--243",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• isbn13 = "978-3-642-12147-0",
• DOI = "doi:10.1007/978-3-642-12148-7_20",
• abstract = "Cartesian Genetic Programming (CGP) is applied to solving differential equations (DE). We illustrate that repeated elements in analytic solutions to DE can be exploited under GP. An analysis is carried out of the search space in tree and CGP frameworks, examining the complexity of different DE problems. Experimental results are provided against benchmark ordinary and partial differential equations. A system of ordinary differential equations (SODE) is solved using multiple outputs from a genome. We discuss best heuristics when generating DE solutions through evolutionary search.",
• notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010 held in conjunction with EvoCOP2010 EvoBIO2010 and EvoApplications2010",

}

Genetic Programming entries for Tom Seaton Gavin Brown Julian F Miller

Citations