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Article

Self Modifying Cartesian Genetic Programming: Fibonacci, Squares, Regression and Summing

Authors:

Julian F. Miller,

Wolfgang BanzhafAuthors Info & Claims

EuroGP '09: Proceedings of the 12th European Conference on Genetic Programming

Pages 133 - 144

https://doi.org/10.1007/978-3-642-01181-8_12

Published: 10 April 2009 Publication History

Abstract

Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It is able to modify its own phenotype during execution of the evolved program. This is done by the inclusion of modification operators in the function set. Here we present the use of the technique on several different sequence generation and regression problems.

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Cited By

Manazir ARaza K(2019)Recent Developments in Cartesian Genetic Programming and its VariantsACM Computing Surveys10.1145/327551851:6(1-29)Online publication date: 28-Jan-2019
https://dl.acm.org/doi/10.1145/3275518
Picek SJakobovic DNeumann FSutton A(2016)Evolving Algebraic Constructions for Designing Bent Boolean FunctionsProceedings of the Genetic and Evolutionary Computation Conference 201610.1145/2908812.2908915(781-788)Online publication date: 20-Jul-2016
https://dl.acm.org/doi/10.1145/2908812.2908915
Miller JTurner AEsparcia-Alcázar A(2015)Cartesian Genetic ProgrammingProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2756571(179-198)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2756571
Show More Cited By

Self Modifying Cartesian Genetic Programming: Fibonacci, Squares, Regression and Summing
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies

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Self-modifying Cartesian Genetic Programming (SMCGP) is a general purpose, graph-based, developmental form of Genetic Programming founded on Cartesian Genetic Programming. In addition to the usual computational functions, it includes functions that can ...

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Information & Contributors

Information

Published In

cover image Guide Proceedings

EuroGP '09: Proceedings of the 12th European Conference on Genetic Programming

April 2009

361 pages

ISBN:9783642011801

Editors:
Leonardo Vanneschi
Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, Milano, Italy 20126
,
Steven Gustafson
GE Global Research, Niskayuna, USA NY 12309
,
Alberto Moraglio
Department of Computer Engineering, University of Coimbra, Coimbra, Portugal 3030
,
Ivanoe Falco
Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR - CNR), Napoli, Italy 80131
,
Marc Ebner
Wilhelm Schickard Institut für Informatik, Eberhard Karls Universität Tübingen, Tübingen, Germany 72076

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 10 April 2009

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Cited By

Manazir ARaza K(2019)Recent Developments in Cartesian Genetic Programming and its VariantsACM Computing Surveys10.1145/327551851:6(1-29)Online publication date: 28-Jan-2019
https://dl.acm.org/doi/10.1145/3275518
Picek SJakobovic DNeumann FSutton A(2016)Evolving Algebraic Constructions for Designing Bent Boolean FunctionsProceedings of the Genetic and Evolutionary Computation Conference 201610.1145/2908812.2908915(781-788)Online publication date: 20-Jul-2016
https://dl.acm.org/doi/10.1145/2908812.2908915
Miller JTurner AEsparcia-Alcázar A(2015)Cartesian Genetic ProgrammingProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2756571(179-198)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2756571
Miller JAlba E(2013)GECCO 2013 tutorialProceedings of the 15th annual conference companion on Genetic and evolutionary computation10.1145/2464576.2464578(715-740)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2464576.2464578
Cordella LDe Stefano CFontanella FMarcelli A(2013)EvoGeneSys, a new evolutionary approach to graph generationApplied Soft Computing10.1016/j.asoc.2012.12.03713:4(1922-1938)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.asoc.2012.12.037
Miller JHarding SMoore J(2012)GECCO 2012 tutorialProceedings of the 14th annual conference companion on Genetic and evolutionary computation10.1145/2330784.2330932(1093-1116)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330784.2330932
Castle TJohnson C(2012)Evolving high-level imperative program trees with strongly formed genetic programmingProceedings of the 15th European conference on Genetic Programming10.1007/978-3-642-29139-5_1(1-12)Online publication date: 11-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-29139-5_1
Lopes RCosta E(2011)The squares problem and a neutrality analysis with ReNCoDeProceedings of the 15th Portugese conference on Progress in artificial intelligence10.5555/2051115.2051134(182-195)Online publication date: 10-Oct-2011
https://dl.acm.org/doi/10.5555/2051115.2051134
Miller JHarding SLanzi P(2011)GECCO 2011 tutorialProceedings of the 13th annual conference companion on Genetic and evolutionary computation10.1145/2001858.2002136(1261-1284)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001858.2002136
Lopes RCosta ELanzi P(2011)Using feedback in a regulatory network computational deviceProceedings of the 13th annual conference on Genetic and evolutionary computation10.1145/2001576.2001778(1499-1506)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001576.2001778
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