By the same authors

A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track. / Clegg, Janet; Walker, James Alfred; Miller, Julian Francis.

GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2. NEW YORK : ASSOC COMPUTING MACHINERY, 2007. p. 1580-1587.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Clegg, J, Walker, JA & Miller, JF 2007, A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track. in GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2. ASSOC COMPUTING MACHINERY, NEW YORK, pp. 1580-1587, GECCO 2007, London, England, 7/07/07.

APA

Clegg, J., Walker, J. A., & Miller, J. F. (2007). A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track. In GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 (pp. 1580-1587). NEW YORK: ASSOC COMPUTING MACHINERY.

Vancouver

Clegg J, Walker JA, Miller JF. A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track. In GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2. NEW YORK: ASSOC COMPUTING MACHINERY. 2007. p. 1580-1587

Author

Clegg, Janet ; Walker, James Alfred ; Miller, Julian Francis. / A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track. GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2. NEW YORK : ASSOC COMPUTING MACHINERY, 2007. pp. 1580-1587

Bibtex - Download

@inproceedings{ff231936708148e2b43760c3eec91ae6,
title = "A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track",
abstract = "Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped to create the offspring. Later Miller and Thomson introduced Cartesian Genetic Programming, which uses directed graphs as a representation to replace the tree structures originally introduced by Koza. Cartesian Genetic Programming has been shown to perform better than the traditional Genetic Programming; but it does not; use crossover to create offspring, it is implemented using mutation only. In this paper a new crossover method in Genetic Programming is introduced. The new technique is based on an adaptation of the Cartesian Genetic Programming representation and is tested oil two simple regression problems. It is shown that by implementing the new crossover technique, convergence is faster than that of using mutation only in the Cartesian Genetic Programming method.",
keywords = "Cartesian Genetic Programming, optimization, crossover techniques, NEUTRALITY, LANDSCAPE",
author = "Janet Clegg and Walker, {James Alfred} and Miller, {Julian Francis}",
year = "2007",
language = "English",
isbn = "978-1-59593-697-4",
pages = "1580--1587",
booktitle = "GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2",
publisher = "ASSOC COMPUTING MACHINERY",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track

AU - Clegg, Janet

AU - Walker, James Alfred

AU - Miller, Julian Francis

PY - 2007

Y1 - 2007

N2 - Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped to create the offspring. Later Miller and Thomson introduced Cartesian Genetic Programming, which uses directed graphs as a representation to replace the tree structures originally introduced by Koza. Cartesian Genetic Programming has been shown to perform better than the traditional Genetic Programming; but it does not; use crossover to create offspring, it is implemented using mutation only. In this paper a new crossover method in Genetic Programming is introduced. The new technique is based on an adaptation of the Cartesian Genetic Programming representation and is tested oil two simple regression problems. It is shown that by implementing the new crossover technique, convergence is faster than that of using mutation only in the Cartesian Genetic Programming method.

AB - Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped to create the offspring. Later Miller and Thomson introduced Cartesian Genetic Programming, which uses directed graphs as a representation to replace the tree structures originally introduced by Koza. Cartesian Genetic Programming has been shown to perform better than the traditional Genetic Programming; but it does not; use crossover to create offspring, it is implemented using mutation only. In this paper a new crossover method in Genetic Programming is introduced. The new technique is based on an adaptation of the Cartesian Genetic Programming representation and is tested oil two simple regression problems. It is shown that by implementing the new crossover technique, convergence is faster than that of using mutation only in the Cartesian Genetic Programming method.

KW - Cartesian Genetic Programming

KW - optimization

KW - crossover techniques

KW - NEUTRALITY

KW - LANDSCAPE

M3 - Conference contribution

SN - 978-1-59593-697-4

SP - 1580

EP - 1587

BT - GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2

PB - ASSOC COMPUTING MACHINERY

CY - NEW YORK

ER -