Smooth symbolic regression: Transformation of symbolic regression into a real-valued optimization problem

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Abstract

The typical methods for symbolic regression produce rather abrupt changes in solution candidates. In this work, we have tried to transform symbolic regression from an optimization problem, with a landscape that is so rugged that typical analysis methods do not produce meaningful results, to one that can be compared to typical and very smooth real-valued problems. While the ruggedness might not interfere with the performance of optimization, it restricts the possibilities of analysis. Here, we have explored different aspects of a transformation and propose a simple procedure to create real-valued optimization problems from symbolic regression problems.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers
EditorsFranz Pichler, Roberto Moreno-Díaz, Alexis Quesada-Arencibia
PublisherSpringer
Pages375-383
Number of pages9
ISBN (Print)9783319273396
DOIs
Publication statusPublished - 2015
Event15th International Conference on Computer Aided Systems Theory, Eurocast 2015 - Las Palmas, Gran Canaria, Spain
Duration: 8 Feb 201513 Feb 2015
http://eurocast2015.fulp.ulpgc.es/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9520
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Computer Aided Systems Theory, Eurocast 2015
Country/TerritorySpain
CityLas Palmas, Gran Canaria
Period08.02.201513.02.2015
Internet address

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