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Recent Developments in Cartesian Genetic Programming and its Variants

Authors:

Khalid RazaAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 51, Issue 6

Article No.: 122, Pages 1 - 29

https://doi.org/10.1145/3275518

Published: 28 January 2019 Publication History

Abstract

Cartesian Genetic Programming (CGP) is a variant of Genetic Programming with several advantages. During the last one and a half decades, CGP has been further extended to several other forms with lots of promising advantages and applications. This article formally discusses the classical form of CGP and its six different variants proposed so far, which include Embedded CGP, Self-Modifying CGP, Recurrent CGP, Mixed-Type CGP, Balanced CGP, and Differential CGP. Also, this article makes a comparison among these variants in terms of population representations, various constraints in representation, operators and functions applied, and algorithms used. Further, future work directions and open problems in the area have been discussed.

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Index Terms

Recent Developments in Cartesian Genetic Programming and its Variants
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Bio-inspired approaches
        Genetic programming

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 51, Issue 6

November 2019

786 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3303862

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering

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Publication History

Published: 28 January 2019

Accepted: 01 September 2018

Revised: 01 April 2018

Received: 01 September 2017

Published in CSUR Volume 51, Issue 6

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https://dl.acm.org/doi/10.1145/3583133.3596305
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