@inproceedings{cd2a773d7a8c42aeb46bc29ec1c38bce,
title = "Interactive genetic algorithms for user interface design",
abstract = "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.",
author = "Quiroz, {Juan C.} and Louis, {Sushil J.} and Anil Shankar and Dascalu, {Sergiu M.}",
year = "2007",
doi = "10.1109/CEC.2007.4424630",
language = "English",
isbn = "9781424413393",
series = "IEEE Congress on Evolutionary Computation",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "1366--1373",
booktitle = "2007 IEEE Congress on Evolutionary Computation, Proceedings",
address = "United States",
note = "IEEE Congress on Evolutionary Computation ; Conference date: 25-09-2007 Through 28-09-2007",
}