Evolution evolves with autoconstruction

Lee Spector, Nicholas Freitag McPhee, Thomas Helmuth, Maggie M. Casale, Julian Oks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In autoconstructive evolutionary algorithms, individuals implement not only candidate solutions to specified computational problems, but also their own methods for variation of offspring. This makes it possible for the variation methods to themselves evolve, which could, in principle, produce a system with an enhanced capacity for adaptation and superior problem solving power. Prior work on autoconsruction has explored a range of system designs and their evolutionary dynamics, but it has not solved hard problems. Here we describe a new approach that can indeed solve at least some hard problems. We present the key components of this approach, including the use of linear genomes for hierarchically structured programs, a diversity-maintaining parent selection algorithm, and the enforcement of diversification constraints on offspring. We describe a software synthesis benchmark problem that our new approach can solve, and we present visualizations of data from single successful runs of autoconstructive vs. non-autoconstructive systems on this problem. While anecdotal, the data suggests that variation methods, and therefore significant aspects of the evolutionary process, evolve over the course of the autoconstructive runs.

Original languageEnglish (US)
Title of host publicationGECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference
EditorsTobias Friedrich
PublisherAssociation for Computing Machinery, Inc
Pages1349-1356
Number of pages8
ISBN (Electronic)9781450343237
DOIs
StatePublished - Jul 20 2016
Event2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion - Denver, United States
Duration: Jul 20 2016Jul 24 2016

Publication series

NameGECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference

Other

Other2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion
Country/TerritoryUnited States
CityDenver
Period7/20/167/24/16

Bibliographical note

Publisher Copyright:
© 2016 ACM.

Keywords

  • Autoconstructive evolution
  • Genetic programming
  • Push

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