Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming

Roman Kalkreuth

2022

Abstract

The search performance of Cartesian Genetic Programming (CGP) relies to a large extent on the sole use of genotypic point mutation in combination with extremely large redundant genotypes. Over the last years, steps have been taken to extend CGP's variation mechanisms by the introduction of advanced methods for recombination and mutation. One branch of these contributions addresses phenotypic variation in CGP. Besides demonstrating the effectiveness of various phenotypic search operators, corresponding analytical experiments backed evidence that phenotypic variation is another approach for achieving effective evolutionary-driven search in CGP. However, recent comparative studies have demonstrated the limitations of phenotypic recombination in Boolean function learning and highlighted the effectiveness of the mutation-only approach. Especially the use of the 1+λ selection strategy with neutral genetic drift has been found superior to recombination-based approaches in this problem domain. Therefore, in this work, we further explore phenotypic mutation in CGP by the introduction and evaluation of two phenotypic mutation operators that are inspired by chromosomal rearrangement. Our initial findings show that our proposed methods can significantly improve the search performance of CGP on various single- and multiple-output Boolean function benchmarks by reducing the number of fitness evaluations needed to find the ideal solution.

Paper Citation

in Harvard Style

Kalkreuth R. (2022). Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming. In Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA; ISBN 978-989-758-611-8, SciTePress, pages 50-61. DOI: 10.5220/0011551000003332

in Bibtex Style

@conference{ecta22,
author={Roman Kalkreuth},
title={Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA},
year={2022},
pages={50-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011551000003332},
isbn={978-989-758-611-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA
TI - Towards Phenotypic Duplication and Inversion in Cartesian Genetic Programming
SN - 978-989-758-611-8
AU - Kalkreuth R.
PY - 2022
SP - 50
EP - 61
DO - 10.5220/0011551000003332
PB - SciTePress