Publication Details

Cartesian Genetic Programming in a Changing Environment

SLANÝ Karel. Cartesian Genetic Programming in a Changing Environment. In: Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015). Lisbon: SciTePress - Science and Technology Publications, 2015, pp. 204-211. ISBN 978-989-758-157-1.
Czech title
Kartézské genetické programování v proměnném prostředí
Type
conference paper
Language
english
Authors
Slaný Karel, Ing. (DCSY FIT BUT)
URL
Keywords

Cartesian Genetic Programming, Age Layered Population Structure, Changing Environment

Abstract

Evolutionary algorithm are prevalently being used in static environments. In a dynamically changing environment an evolutionary algorithm must be also able to cope with the changes of the environment. This paper describes an algorithm based on Cartesian Genetic Programming (CGP) that is used to design and optimise a solution in a simulated symbolic regression problem in a changing environment. A modified version of the Age-Layered Population Structure (ALPS) algorithm is being used in cooperation with CGP. It is shown that the usage of ALPS can improve the performance on of CGP when solving problems in a changing environment.

Published
2015
Pages
204-211
Proceedings
Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)
Conference
International Conference on Evolutionary Computation Theory and Applications 2015, Lisbon, PT
ISBN
978-989-758-157-1
Publisher
SciTePress - Science and Technology Publications
Place
Lisbon, PT
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB10980,
   author = "Karel Slan\'{y}",
   title = "Cartesian Genetic Programming in a Changing Environment",
   pages = "204--211",
   booktitle = "Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015)",
   year = 2015,
   location = "Lisbon, PT",
   publisher = "SciTePress - Science and Technology Publications",
   ISBN = "978-989-758-157-1",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/10980"
}
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