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A Study of Direct and Indirect Encoding in Phenotype-Genotype Relationships

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12855))

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Abstract

This paper examines phenotype and genotype mappings that are biologically inspired. These types of coding are used in evolutionary computation. Direct and indirect encoding are studied. The determination of genotype and phenotype relationships and the connection to genetic algorithms, evolutionary programming and biology are examined in the light of newer advances. The NEAT and HyperNEAT algorithms are applied to the 2D Walker [41] problem of an agent learning how to walk. Results and findings are discussed, and conclusions are given. Indirect coding did not improve the situation. This paper shows that indirect coding is not useful in every situation.

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Notes

  1. 1.

    Available at https://sharpneat.sourceforge.io/.

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Acknowledgments

This work was supported by financial support of research project NPU I No. MSMT-7778/2014 by the Ministry of Education of the Czech Republic, by the European Regional Development Fund under the Project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089 and by resources of A.I. Lab research group at Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).

Author information

Authors and Affiliations

  1. Department of Computer Information Systems, University of Malta, Msida, Malta

    Clyde Meli, Vitezslav Nezval & Anthony Spiteri Staines

  2. Faculty of Applied Informatics, Department of Informatics and Artificial Intelligence, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

  3. Department of Communications and Computer Engineering, University of Malta, Msida, Malta

    Victor Buttigieg

Authors
  1. Clyde Meli
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  2. Vitezslav Nezval
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  3. Zuzana Kominkova Oplatkova
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  4. Victor Buttigieg
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  5. Anthony Spiteri Staines
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Corresponding author

Correspondence to Clyde Meli .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Meli, C., Nezval, V., Oplatkova, Z.K., Buttigieg, V., Staines, A.S. (2021). A Study of Direct and Indirect Encoding in Phenotype-Genotype Relationships. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12855. Springer, Cham. https://doi.org/10.1007/978-3-030-87897-9_27

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  • DOI: https://doi.org/10.1007/978-3-030-87897-9_27

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