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Autoconstructive evolution for structural problems

Published: 07 July 2012 Publication History

Abstract

While most hyper-heuristics search for a heuristic that is later used to solve classes of problems, autoconstructive evolution represents an alternative which simultaneously searches both heuristic and solution space. In this study we contrast autoconstructive evolution, in which intergenerational variation is accomplished by the evolving programs themselves, with a genetic programming system, PushGP, to understand the dynamics of this hybrid approach. A problem size scaling analysis of these genetic programming techniques is performed on structural problems. These problems involve fewer domain-specific features than most model problems while maintaining core features representative of program search. We use two such problems, Order and Majority, to study autoconstructive evolution in the Push programming language.

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Cited By

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  • (2017)Recent developments in autoconstructive evolutionProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3082058(1154-1156)Online publication date: 15-Jul-2017
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  • (2016)Evolution Evolves with AutoconstructionProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2931727(1349-1356)Online publication date: 20-Jul-2016
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cover image ACM Conferences
GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
July 2012
1586 pages
ISBN:9781450311786
DOI:10.1145/2330784
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 ACM 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]

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Publication History

Published: 07 July 2012

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Author Tags

  1. PushGP
  2. autoconstruction
  3. majority
  4. order
  5. push
  6. structural problems

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  • Research-article

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GECCO '12
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GECCO '12: Genetic and Evolutionary Computation Conference
July 7 - 11, 2012
Pennsylvania, Philadelphia, USA

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Cited By

View all
  • (2017)Recent developments in autoconstructive evolutionProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3082058(1154-1156)Online publication date: 15-Jul-2017
  • (2017)State Flipping Based Hyper-Heuristic for Hybridization of Nature Inspired AlgorithmsArtificial Intelligence and Soft Computing10.1007/978-3-319-59063-9_30(337-346)Online publication date: 27-May-2017
  • (2016)Evolution Evolves with AutoconstructionProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2931727(1349-1356)Online publication date: 20-Jul-2016
  • (2015)Expressive Genetic ProgrammingProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2756578(409-434)Online publication date: 11-Jul-2015
  • (2014)Expressive genetic programmingProceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation10.1145/2598394.2605350(581-606)Online publication date: 12-Jul-2014
  • (2013)Expressive genetic programmingProceedings of the 15th annual conference companion on Genetic and evolutionary computation10.1145/2464576.2480806(683-714)Online publication date: 6-Jul-2013
  • (2013)Is the meta-EA a viable optimization method?Proceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2465806(1533-1540)Online publication date: 6-Jul-2013
  • (2012)Expressive genetic programmingProceedings of the 14th annual conference companion on Genetic and evolutionary computation10.1145/2330784.2330926(983-1012)Online publication date: 7-Jul-2012

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