Shorter Fitness Preserving Genetic Programs

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2000Publisher:Springer Berlin Heidelberg

Authors: Anikó Ekárt;

doi: 10.1007/10721187_5

Shorter Fitness Preserving Genetic Programs

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Abstract

In the paper a method that moderates code growth in genetic programming is presented. The addressed problem is symbolic regression. A special mutation operator is used for the simplification of programs. If every individual program in each generation is simplified, then the performance of the genetic programming system is slightly worsened. But if simplification is applied as a mutation operator, more compact solutions of the same or better accuracy can be obtained.

Related Organizations

MTA Institute for Computer Science and Control
Hungary
Hungarian Academy of Sciences
Hungary

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