Genetic Programming Based Evolvement of Models of Models

Mariia Semenkina; Bogdan Burlacu; Michael Affenzeller

doi:10.1007/978-3-030-45093-9_47

Genetic Programming Based Evolvement of Models of Models

Mariia Semenkina, Bogdan Burlacu, Michael Affenzeller

Research Center Hagenberg

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

1 Zitat (Scopus)

Abstract

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.

Originalsprache	Englisch
Titel	Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
Redakteure/-innen	Roberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
Herausgeber (Verlag)	Springer
Seiten	387-395
Seitenumfang	9
ISBN (Print)	9783030450922
DOIs	https://doi.org/10.1007/978-3-030-45093-9_47
Publikationsstatus	Veröffentlicht - 2020
Veranstaltung	17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 - Las Palmas de Gran Canaria, Spanien Dauer: 17 Feb. 2019 → 22 Feb. 2019

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	12013 LNCS
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	17th International Conference on Computer Aided Systems Theory, EUROCAST 2019
Land/Gebiet	Spanien
Ort	Las Palmas de Gran Canaria
Zeitraum	17.02.2019 → 22.02.2019

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10.1007/978-3-030-45093-9_47

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Semenkina, M., Burlacu, B., & Affenzeller, M. (2020). Genetic Programming Based Evolvement of Models of Models. in R. Moreno-Díaz, A. Quesada-Arencibia, & F. Pichler (Hrsg.), Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers (S. 387-395). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12013 LNCS). Springer. https://doi.org/10.1007/978-3-030-45093-9_47

Semenkina, Mariia ; Burlacu, Bogdan ; Affenzeller, Michael. / Genetic Programming Based Evolvement of Models of Models. Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz ; Alexis Quesada-Arencibia ; Franz Pichler. Springer, 2020. S. 387-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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{\textquoteright}s knowledge about the problem in hand has been reviewed. In this work a map of building block{\textquoteright}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.",

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Semenkina, M, Burlacu, B & Affenzeller, M 2020, Genetic Programming Based Evolvement of Models of Models. in R Moreno-Díaz, A Quesada-Arencibia & F Pichler (Hrsg.), Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 12013 LNCS, Springer, S. 387-395, 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019, Las Palmas de Gran Canaria, Spanien, 17.02.2019. https://doi.org/10.1007/978-3-030-45093-9_47

Genetic Programming Based Evolvement of Models of Models. / Semenkina, Mariia; Burlacu, Bogdan ; Affenzeller, Michael.
Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz; Alexis Quesada-Arencibia; Franz Pichler. Springer, 2020. S. 387-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12013 LNCS).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

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AU - Burlacu, Bogdan

AU - Affenzeller, Michael

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AB - 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.

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KW - Models of Models

KW - Symbolic Regression

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Semenkina M, Burlacu B , Affenzeller M. Genetic Programming Based Evolvement of Models of Models. in Moreno-Díaz R, Quesada-Arencibia A, Pichler F, Hrsg., Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Springer. 2020. S. 387-395. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-45093-9_47

Genetic Programming Based Evolvement of Models of Models

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