The effect of user interaction mechanisms in multi-objective IGA

Alexandra Melike Brintrup, Hideyuki Takagi

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

4 Citations (Scopus)

Abstract

In this paper four mechanisms, fine and coarse grained fitness rating, linguistic evaluation and active user intervention are compared for use in the multi-objective IGA. The interaction mechanisms are tested on the ergonomic chair design problem. The active user intervention mechanism provided the best fitness convergence but resulted in the least diverse results. The fine grained evaluation provided a good blend of fitness convergence and diversity while the popular coarse grained discrete rating provided poor results. Linguistic evaluation resulted in poor qualitative fitness despite its fast speed of evaluation. The significant differences between interaction mechanisms show the need for further research.

Original languageEnglish
Title of host publicationProceedings of GECCO 2007
Subtitle of host publicationGenetic and Evolutionary Computation Conference, Companion Material
Pages2629-2632
Number of pages4
DOIs
Publication statusPublished - Aug 27 2007
Event9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom
Duration: Jul 7 2007Jul 11 2007

Publication series

NameProceedings of GECCO 2007: Genetic and Evolutionary Computation Conference, Companion Material

Other

Other9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
CountryUnited Kingdom
CityLondon
Period7/7/077/11/07

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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