Genetic Programming Based Evolvement of Models of Models

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung


The main idea of this paper is to use Simple Symbolic Formulas generated offline with the help of the deterministic function extraction algorithm as building blocks for Genetic Programming. This idea comparison to Automatically Defined Functions approach was considered. A possibility to take into consideration an expert’s knowledge about the problem in hand has been reviewed. In this work a map of building block’s set is generated by means of clustering. All distances between blocks are calculated offline by using a special metric for symbolic expressions. A mutation operator in Genetic Programming was modified for work with this kind of nodes. The effectiveness of this approach was evaluated on benchmark as well as on real world problems.

TitelComputer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
Redakteure/-innenRoberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
Herausgeber (Verlag)Springer
ISBN (Print)9783030450922
PublikationsstatusVeröffentlicht - 2020
Veranstaltung17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 - Las Palmas de Gran Canaria, Spanien
Dauer: 17 Feb. 201922 Feb. 2019


NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band12013 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349


Konferenz17th International Conference on Computer Aided Systems Theory, EUROCAST 2019
OrtLas Palmas de Gran Canaria


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