skip to main content
10.1145/3319619.3321954acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
research-article

Genetic improvement of data gives binary logarithm from sqrt

Published:13 July 2019Publication History

ABSTRACT

Automated search in the form of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), plus manual code changes, transforms 512 Newton-Raphson floating point start numbers from an open source GNU C library, glibc, table driven square root function to create a new bespoke custom mathematical implementation of double precision binary logarithm log2 for C in seconds.

Skip Supplemental Material Section

Supplemental Material

References

  1. Nikolaus Hansen and Andreas Ostermeier. 2001. Completely Derandomized Self-Adaptation in Evolution Strategies. Evolutionary Computation 9, 2 (Summer 2001), 159--195. https://doi.org/ Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. W. B. Langdon. 2018. Evolving Square Root into Binary Logarithm. Technical Report RN/18/05. University College, London, London, UK. http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/RN_18_05.pdfGoogle ScholarGoogle Scholar
  3. William B. Langdon and Mark Harman. 2015. Optimising Existing Software with Genetic Programming. IEEE Transactions on Evolutionary Computation 19, 1 (Feb. 2015), 118--135. https://doi.org/Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. William B. Langdon and Justyna Petke. 2018. Evolving Better Software Parameters. In SSBSE 2018 Hot off the Press Track (LNCS), Thelma Elita Colanzi and Phil McMinn (Eds.), Vol. 11036. Springer, Montpellier, France, 363--369. https://doi.org/Google ScholarGoogle Scholar
  5. William B. Langdon, Justyna Petke, and Ronny Lorenz. 2018. Evolving better RNAfold structure prediction. In EuroGP 2018 (LNCS), Mauro Castelli et al. (Eds.), Springer Verlag, 220--236. https://doi.org/Google ScholarGoogle Scholar
  6. Justyna Petke, Saemundur O. Haraldsson, Mark Harman, William B. Langdon, David R. White, and John R. Woodward. 2018. Genetic Improvement of Software: a Comprehensive Survey. IEEE Transactions on Evolutionary Computation 22, 3 (June 2018), 415--432. https://doi.org/Google ScholarGoogle Scholar
  7. David Robert White, Andrea Arcuri, and John A. Clark. 2011. Evolutionary Improvement of Programs. IEEE TEVC 15, 4 (2011), 515--538. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Genetic improvement of data gives binary logarithm from sqrt

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
      July 2019
      2161 pages
      ISBN:9781450367486
      DOI:10.1145/3319619

      Copyright © 2019 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 July 2019

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate1,669of4,410submissions,38%

      Upcoming Conference

      GECCO '24
      Genetic and Evolutionary Computation Conference
      July 14 - 18, 2024
      Melbourne , VIC , Australia

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader