An analysis of diversity of constants of genetic programming

Authors:
Conor Ryan;Maarten Keijzer
Affiliations:
CSIS Dept., University of Limerick, Ireland;CS Dept., Free University, Amsterdam
Venue:
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Year:
2003

Citing 5
Cited 11

Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
Genetic programming in C++: implementation issues

Advances in genetic programming
Evolutionary identification of macro-mechanical models

Advances in genetic programming
The GA-P: A Genetic Algorithm and Genetic Programming Hybrid

IEEE Expert: Intelligent Systems and Their Applications
Genetic Programming, Ensemble Methods and the Bias/Variance Tradeoff - Introductory Investigations

Proceedings of the European Conference on Genetic Programming

Constant generation for the financial domain using grammatical evolution

GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Heterogeneous cooperative coevolution: strategies of integration between GP and GA

Proceedings of the 8th annual conference on Genetic and evolutionary computation
Context-aware mutation: a modular, context aware mutation operator for genetic programming

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Constant creation in grammatical evolution

International Journal of Innovative Computing and Applications
Using differential evolution for symbolic regression and numerical constant creation

Proceedings of the 10th annual conference on Genetic and evolutionary computation
Abstract functions and lifetime learning in genetic programming for symbolic regression

Proceedings of the 12th annual conference on Genetic and evolutionary computation
Open issues in genetic programming

Genetic Programming and Evolvable Machines
Learning weights in genetic programs using gradient descent for object recognition

EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Systematic adoption of genetic programming for deriving software performance curves

ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Repairing fractures between data using genetic programming-based feature extraction: A case study in cancer diagnosis

Information Sciences: an International Journal
Effects of constant optimization by nonlinear least squares minimization in symbolic regression

Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper conducts an investigation into the manner in which constants evolve during the course of GP run. It starts by describing an intuitive Gaussian type mutation for constants and showing that its ability to produce small changes in individuals leads to a high performance. It then demonstrates the surprising result that, in a selection of real world problems, simple random mutation performs better. The paper then finishes with an analysis of the diversity of constants in the population, and the manner in which this changes over time.