Skip to main content
SpringerLink
Log in

Biological evolution as a paradigm for performance driven design processes

  • Track 13: Biological Information And Neural Network
  • Conference paper
  • First Online:
Computing in the 90's (Great Lakes CS 1989)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 507))

Included in the following conference series:

  • 111 Accesses

Abstract

The application of evolutionary processes to the problem of automated design is explored. A feature detector component for a pattern recognition system is used as an example of the automated design process. Results obtained from applying the resultant detector system to the problem of character recognition are discussed.

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.

References

  1. L. Davis, Genetic Algorithms and Simulated Annealing, Pitman, London, 1987.

    Google Scholar 

  2. A. M. Gillies, "Machine learning procedures for generating image domain feature detectors", Ph.D. Dissertation, University of Michigan, Ann Arbor, 1985.

    Google Scholar 

  3. D. E. Goldberg, Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Mass., 1989.

    Google Scholar 

  4. J. H. Holland, Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, 1975.

    Google Scholar 

  5. M. M. Rizki and M. Conrad, "Computing the theory of evolution", Physica 22D, 1986.

    Google Scholar 

  6. J. Serra, Image Analysis and Mathematical Morphology, Academic Press, London, 1982.

    Google Scholar 

  7. F. W. M. Stentiford, "Automatic feature design for optical character recognition using an evolutionary search procedure", IEEE PAMI-7, No. 3, 1985.

    Google Scholar 

  8. L. A. Tamburino, M. M. Rizki, "Automatic generation of binary features", IEEE Aerospace and Electronics Magazine, September 1989.

    Google Scholar 

  9. L. A. Tamburino, M. M. Rizki and M. A. Zmuda, "Computational resource management in supervised learning systems", NAECON, Vol. 3, 1989.

    Google Scholar 

  10. L. A. Tamburino, M. M. Rizki, W. VanValkenburgh, "Automated feature detection using evolutionary learning processes", NAECON, Vol. 3, 1989.

    Google Scholar 

  11. L. Uhr and C. Vossler, "A pattern-recognition program that generates, evaluates, and adjusts its own operators", in Computers and Thought, ed. E. A. Feigenbaum and J. Feldman, Krieger Publishing Co., Malabar, FL., 1981.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Wright State University, 45435, Dayton, Ohio

    Mateen M. Rizki & Michael A. Zmuda

  2. WRDC/AAAT, Wright-Patterson Air Force Base, 45433, Dayton, Ohio

    Louis A. Tamburino

Authors
  1. Mateen M. Rizki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Louis A. Tamburino
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael A. Zmuda
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Naveed A. Sherwani Elise de Doncker John A. Kapenga

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Rizki, M.M., Tamburino, L.A., Zmuda, M.A. (1991). Biological evolution as a paradigm for performance driven design processes. In: Sherwani, N.A., de Doncker, E., Kapenga, J.A. (eds) Computing in the 90's. Great Lakes CS 1989. Lecture Notes in Computer Science, vol 507. Springer, New York, NY. https://doi.org/10.1007/BFb0038519

Download citation

  • DOI: https://doi.org/10.1007/BFb0038519

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97628-0

  • Online ISBN: 978-0-387-34815-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation