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Serendipitous scaffolding to improve a genetic algorithm's speed and quality
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2018 (English)In: GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, Inc , 2018, p. 959-966Conference paper (Refereed)
Abstract [en]

A central challenge to evolutionary computation is enabling techniques to evolve increasingly complex target end products. Frequently, direct approaches that reward only the target end product itself are not successful because the path between the starting conditions and the target end product traverses through a complex fitness landscape, where the directly accessible intermediary states may be require deleterious or even simply neutral mutations. As such, a host of techniques have sprung up to support evolutionary computation techniques taking these paths. One technique is scaffolding where intermediary targets are used to provide a path from the starting state to the end state. While scaffolding can be successful within well-understood domains it also poses the challenge of identifying useful intermediaries. Within this paper we first identify some shortcomings of scaffolding approaches ' namely, that poorly selected intermediaries may in fact hurt the evolutionary computation's chance of producing the desired target end product. We then describe a light-weight approach to selecting intermediate scaffolding states that improve the efficacy of the evolutionary computation. © 2018 Association for Computing Machinery.

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2018. p. 959-966
Keywords [en]
Evolution, Genetic Algorithms, Optimization, Scaffolding, Calculations, Complex targets, Direct approach, Enabling techniques, Evolutionary computation techniques, Fitness landscape, Intermediary state, Scaffolds
National Category
Evolutionary Biology Computer Sciences
Identifiers
URN: urn:nbn:se:du-37166DOI: 10.1145/3205455.3205617Scopus ID: 2-s2.0-85050645480ISBN: 9781450356183 (print)OAI: oai:DiVA.org:du-37166DiVA, id: diva2:1557904
Conference
GECCO '18-Genetic and Evolutionary Computation Conference July 2018
Note

Export Date: 26 May 2021; Conference Paper

Available from: 2021-05-27 Created: 2021-05-27 Last updated: 2021-05-27Bibliographically approved

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Hintze, Arend

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf