Skip to main content
SpringerLink
Log in
Book cover

International Conference on Computer Aided Systems Theory

EUROCAST 2019: Computer Aided Systems Theory – EUROCAST 2019 pp 387–395Cite as

Genetic Programming Based Evolvement of Models of Models

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12013))

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.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Koza J.: Simultaneous discovery of reusable detectors and subroutines using genetic programming. In: Proceedings of the 5th International Conference on Genetic Algorithms, ICGA 1993, pp. 295–302. Morgan Kaufmann, University of Illinois at Urbana-Champaign (1993)

    Google Scholar 

  2. Koza, J.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  3. Niimi A., Tazaki, E.: Genetic programming combined with association rule algorithm for decision tree construction. In: Proceedings of Fourth International Conference on Knowledge-based Intelligent Engineering Systems and Allied Technologies, Brighton, UK, pp. 746–749 (2000)

    Google Scholar 

  4. McConaghy, T.: FFX: fast, scalable, deterministic symbolic regression technology. In: Riolo, R., Vladislavleva, E., Moore, J. (eds.) Genetic Programming Theory and Practice IX, pp. 235–260. Springer, New York (2011). https://doi.org/10.1007/978-1-4614-1770-5_13

    Chapter  Google Scholar 

  5. Kammerer, L., Kronberger, G., Burlacu, B., Winkler, S.M., Kommenda, M., Affenzeller, M.: Symbolic regression by exhaustive search – reducing the search space using syntactical constraints and efficient semantic structure deduplication. In: Banzhaf, W., Goodman, E., Sheneman, L., Trujillo, L., Worzel, B. (eds.) Genetic Programming Theory and Practice XVII. Springer, New York (2019). https://doi.org/10.1007/978-3-030-39958-0

    Chapter  Google Scholar 

  6. Zojaji, Z., Ebadzadeh, M.M.: Semantic schema modeling for genetic programming using clustering of building blocks. Appl. Intell. 48(6), 1442–1460 (2017). https://doi.org/10.1007/s10489-017-1052-7

    Article  Google Scholar 

  7. Valiente, G.: An efficient bottom-up distance between trees. In: Proceedings of International Symposium on String Processing and Information Retrieval, Laguna de San Rafael, Chile (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Heuristic and Evolutionary Algorithms Laboratory (HEAL), University of Applied Sciences Upper Austria, Softwarepark 11, 4232, Hagenberg, Austria

    Mariia Semenkina, Bogdan Burlacu & Michael Affenzeller

  2. Johannes Kepler University, Altenberger Straße 69, 4040, Linz, Austria

    Mariia Semenkina, Bogdan Burlacu & Michael Affenzeller

Authors
  1. Mariia Semenkina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bogdan Burlacu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael Affenzeller
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mariia Semenkina .

Editor information

Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Semenkina, M., Burlacu, B., Affenzeller, M. (2020). Genetic Programming Based Evolvement of Models of Models. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2019. EUROCAST 2019. Lecture Notes in Computer Science(), vol 12013. Springer, Cham. https://doi.org/10.1007/978-3-030-45093-9_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-45093-9_47

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45092-2

  • Online ISBN: 978-3-030-45093-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation