Publication detail

A Comparative Study on Crossover in Cartesian Genetic Programming

HUSA, J. KALKREUTH, R.

Original Title

A Comparative Study on Crossover in Cartesian Genetic Programming

Type

conference paper

Language

English

Original Abstract

Cartesian Genetic Programming is often used with mutation as the sole genetic operator. Compared to the comprehensive and detailed knowledge about the effect and use of mutation in CGP, the use of crossover has been less investigated and studied. In this paper, we present a comparative study of previously proposed crossover techniques for Cartesian Genetic Programming. This work also includes the proposal of a new crossover technique which swaps block of the CGP phenotype between two selected parents. The experiments of our study open a new perspective on comparative studies on crossover in CGP and its challenges. Our results show that it is possible for a crossover operator to outperform the standard (1 + lambda) strategy on a limited number of tasks. The question of finding a universal crossover operator in CGP remains open.

Keywords

Cartesian Genetic Programming,Crossover,Comparative Study

Authors

HUSA, J.; KALKREUTH, R.

Released

2. 3. 2018

Publisher

Springer International Publishing

Location

Cham

ISBN

978-3-319-77553-1

Book

Genetic Programming 21st European Conference, EuroGP 2018, Proceedings

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Year of study

10781

Number

1

State

Federal Republic of Germany

Pages from

203

Pages to

219

Pages count

17

URL

https://www.fit.vut.cz/research/publication/11555/

BibTex

@inproceedings{BUT154999,
  author="Jakub {Husa} and Roman {Kalkreuth}",
  title="A Comparative Study on Crossover in Cartesian Genetic Programming",
  booktitle="Genetic Programming 21st European Conference, EuroGP 2018, Proceedings",
  year="2018",
  journal="Lecture Notes in Computer Science",
  volume="10781",
  number="1",
  pages="203--219",
  publisher="Springer International Publishing",
  address="Cham",
  doi="10.1007/978-3-319-77553-1\{_}13",
  isbn="978-3-319-77553-1",
  issn="0302-9743",
  url="https://www.fit.vut.cz/research/publication/11555/"
}