skip to main content
10.1145/1276958.1277243acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
Article

A simple genetic algorithm for reducible complexity

Published: 07 July 2007 Publication History

Abstract

Challenges are often lofted to explain how gradualistic evolution can evolve systems where function ceases with the removal of any of their multiple parts. We present a genetic algorithm (GA) example using a dynamic fitness function. Given clear definitions of relevant terms, the GA produces such complex systems.

References

[1]
The TalkOrigins Archive. http://www.talkorigins.org.
[2]
Graham, L., and Oppacher, F. Speciation through Exaptation. In Proceedings of IEEE ALife'07. 2007.

Index Terms

  1. A simple genetic algorithm for reducible complexity

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 July 2007

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. complexity
    2. evolution
    3. genetic algorithms

    Qualifiers

    • Article

    Conference

    GECCO07
    Sponsor:

    Acceptance Rates

    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 173
      Total Downloads
    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 16 Feb 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media