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Publication Details

Coevolution in Cartesian Genetic Programming

DRAHOŠOVÁ Michaela and SEKANINA Lukáš. Coevolution in Cartesian Genetic Programming. In: Proc. of the 15th European Conference on Genetic Programming. Lecture Notes in Computer Science, vol. 7244. Heidelberg: Springer Verlag, 2012, pp. 182-193. ISBN 978-3-642-29138-8. Available from: http://www.springerlink.com/content/e47453258l284p60/fulltext.pdf
Czech title
Koevoluce v kartézském genetickém programování
Type
conference paper
Language
english
Authors
URL
Keywords
Cartesian genetic programming, coevolution, fitness modeling, fitness predictors, symbolic regression.

Abstract
Cartesian genetic programming (CGP) is a branch of genetic programming which has been utilized in various applications. This paper proposes to introduce coevolution to CGP in order to accelerate the task of symbolic regression. In particular, fitness predictors which are small subsets of the training set are coevolved with CGP programs. It is shown using five symbolic regression problems that the (median) execution time can be reduced 2-5 times in comparison with the standard CGP.

Published
2012
Pages
182-193
Proceedings
Proc. of the 15th European Conference on Genetic Programming
Series
Lecture Notes in Computer Science
Volume
7244
Conference
15th European Conference on Genetic Programming, Malaga, ES
ISBN
978-3-642-29138-8
Publisher
Springer Verlag
Place
Heidelberg, DE
DOI
BibTeX
@INPROCEEDINGS{FITPUB9832,
   author = "Michaela Draho\v{s}ov\'{a} and Luk\'{a}\v{s} Sekanina",
   title = "Coevolution in Cartesian Genetic Programming",
   pages = "182--193",
   booktitle = "Proc. of the 15th European Conference on Genetic Programming",
   series = "Lecture Notes in Computer Science",
   volume = 7244,
   year = 2012,
   location = "Heidelberg, DE",
   publisher = "Springer Verlag",
   ISBN = "978-3-642-29138-8",
   doi = "10.1007/978-3-642-29139-5\_16",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/9832"
}
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