Skip to main content
SpringerLink
Log in

A principle of minimum complexity in evolution

  • Adaptation And Evolution In General
  • Conference paper
  • First Online:
Parallel Problem Solving from Nature (PPSN 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 496))

Included in the following conference series:

Abstract

This paper presents a principle of minimum complexity in evolving systems. Minimum complexity is supported by results and observations from genetic algorithm research and information complexity theory. This paper introduces minimum complexity and presents quantitative evidence for minimum complexity in messy genetic evolution. There also appears to be a strong correlation with our theory and what is observed in biological genetics.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

6.0 References

  • Deb, K., (1990) "String Growth in Messy Genetic Algorithms," TGCA Report No. 90006, June 1990, University of Alabama, Tuscaloosa.

    Google Scholar 

  • Goldberg, D., (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, 1989.

    Google Scholar 

  • Goldberg, D., Korb, B., Deb, K., (1989) "Messy Genetic Algorithms: Motivation, Analysis, and First Results," TGCA Report No. 89003, May 1989, University of Alabama, Tuscaloosa.

    Google Scholar 

  • Goldberg, D., Deb, K., Korb, B. (1990) "An Investigation of Messy Genetic Algorithms," TGCA Report No. 90005, May 1990, University of Alabama, Tuscaloosa.

    Google Scholar 

  • Holland, J., (1975) Adaptation in natural and artificial systems. Ann Arbor, MI: University of Michigan Press.

    Google Scholar 

  • Kasper, F., Schuster, H., (1987) "Easily calculable measure for the complexity of spatiotemporal patterns," Physical Review A, Vol. 36, No. 2, July 15, 1987.

    Google Scholar 

  • Kolmogorov, A., (1965) Problems in Information Transmission, 1, 1 (1965).

    Google Scholar 

  • Kreitman, M., (1983) "Nucleotide polymorphism at the alcohol dehydrogenase locus of Drosophila melanogaster," Nature, vol. 304, 4 August 1983.

    Google Scholar 

  • Lempel, A., Ziv, J., IEEE Trans. Inf. Theory IT-22, 75 (1976).

    Article  Google Scholar 

  • Tashima, Calobretta, Torelli, Scofield, Maizeland, and Saunders, (1981) "Presence of a highly repetitive and widely dispersed DNA sequence in the human genome," Proc. Natl. Acad. Sci. USA, Vol. 78, No. 3, pp. 1508–1512, March 1981, Biochemistry.

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. U.S. Army Strategic Defense Command, Advanced Technology Directorate, Huntsville, Alabama

    Luis R. Lopez

  2. Center for Applied Optics, University of Alabama Huntsville, Huntsville, Alabama

    H. John Caulfield

Authors
  1. Luis R. Lopez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. John Caulfield
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Hans-Paul Schwefel Reinhard Männer

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lopez, L.R., Caulfield, H.J. (1991). A principle of minimum complexity in evolution. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029782

Download citation

  • DOI: https://doi.org/10.1007/BFb0029782

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54148-6

  • Online ISBN: 978-3-540-70652-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation