skip to main content
10.1145/3520304.3528958acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
poster

Environments with local scopes for modules in genetic programming

Published:19 July 2022Publication History

ABSTRACT

Scoped environments are used in various programming languages to provide contexts within which a function's code can bind values and perform computations with them, without affecting bindings used by the rest of the program. The PushGP genetic programming system, which has produced state-of-the-art results in application areas, including software synthesis, allows programs to label sequences of instructions as modules. However, those modules can also modify bindings used by the rest of the program. This increases module coupling and might therefore make modular programs less evolvable than they otherwise could be. To rectify this, and to ensure that modules return single values, we implement scoped environments in PushGP, using a method that allows for the dynamic definition of arbitrary modules in a multi-type setting. We demonstrate that the use of scoped environments leads to an increase in the success rates for multiple software synthesis problems.

References

  1. Thomas Helmuth and Peter Kelly. 2021. PSB2: the second program synthesis benchmark suite. In Proceedings of the Genetic and Evolutionary Computation Conference. 785--794.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Thomas Helmuth, Nicholas Freitag McPhee, Edward Pantridge, and Lee Spector. 2017. Improving generalization of evolved programs through automatic simplification. In Proceedings of the Genetic and Evolutionary Computation Conference. 937--944.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Thomas Helmuth and Lee Spector. 2015. General program synthesis benchmark suite. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. 1039--1046.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Maarten Keijzer, Conor Ryan, and Mike Cattolico. 2004. Run transferable libraries---learning functional bias in problem domains. In Genetic and Evolutionary Computation Conference. Springer, 531--542.Google ScholarGoogle ScholarCross RefCross Ref
  5. John R Koza and John R Koza. 1992. Genetic programming: on the programming of computers by means of natural selection. Vol. 1. MIT press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. William La Cava, Lee Spector, and Kourosh Danai. 2016. Epsilon-lexicase selection for regression. In Proceedings of the Genetic and Evolutionary Computation Conference 2016. 741--748.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Edward Pantridge, Thomas Helmuth, and Lee Spector. 2020. Comparison of Linear Genome Representations for Software Synthesis. Genetic Programming Theory and Practice XVII (2020), 255.Google ScholarGoogle Scholar
  8. Anil Kumar Saini and Lee Spector. 2021. GLEAM: genetic learning by extraction and absorption of modules. In Proceedings of the Genetic and Evolutionary Computation Conference Companion. 263--264.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Dominik Sobania, Dirk Schweim, and Franz Rothlauf. 2021. Recent Developments in Program Synthesis with Evolutionary Algorithms. arXiv preprint arXiv:2108.12227 (2021).Google ScholarGoogle Scholar
  10. Lee Spector, Jon Klein, and Maarten Keijzer. 2005. The push3 execution stack and the evolution of control. In Proceedings of the 7th annual conference on Genetic and evolutionary computation. 1689--1696.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Lee Spector and Alan Robinson. 2002. Genetic programming and autoconstructive evolution with the push programming language. Genetic Programming and Evolvable Machines 3, 1 (2002), 7--40.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. John Mark Swafford, Erik Hemberg, Michael O'Neill, and Anthony Brabazon. 2012. Analyzing module usage in grammatical evolution. In International Conference on Parallel Problem Solving from Nature. Springer, 347--356.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. James Alfred Walker and Julian Francis Miller. 2008. The automatic acquisition, evolution and reuse of modules in cartesian genetic programming. IEEE Transactions on Evolutionary Computation 12, 4 (2008), 397--417.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Environments with local scopes for modules in genetic programming

      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 '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
        July 2022
        2395 pages
        ISBN:9781450392686
        DOI:10.1145/3520304

        Copyright © 2022 Owner/Author

        Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 July 2022

        Check for updates

        Qualifiers

        • poster

        Acceptance Rates

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

        Upcoming Conference

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

        • Downloads (Last 12 months)5
        • Downloads (Last 6 weeks)0

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader