Interactive genetic algorithms for user interface design

Juan C. Quiroz*, Sushil J. Louis, Anil Shankar, Sergiu M. Dascalu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

42 Citations (Scopus)


We attack the problem of user fatigue in using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algorithm combines computable user interface design metrics with subjective user input to guide evolution. Individuals in our population represent interface specifications and we compute an individual's fitness from a weighted combination of user input and user interface design guidelines. Results from our preliminary study involving three users indicate that users are able to effectively bias evolution towards user interface designs that reflect both user preferences and computed guideline metrics. Furthermore, we can reduce fatigue, defined by the number of choices needing to be made by the human designer, by doing two things. First, asking the user to pick just two (the best and worst) user interfaces from among a subset of nine shown. Second, asking the user to make the choice once every t generations, instead of every single generation. Our goal is to provide interface designers with an interactive tool that can be used to explore innovation and creativity in the design space of user interfaces.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Print)9781424413393
Publication statusPublished - 2007
Externally publishedYes
EventIEEE Congress on Evolutionary Computation - Singapore, Singapore
Duration: 25 Sept 200728 Sept 2007

Publication series

NameIEEE Congress on Evolutionary Computation


ConferenceIEEE Congress on Evolutionary Computation


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