Interactive genetic algorithms for user interface design

Abstract — We attack the problem of user fatigue in de-veloping an interactive genetic algorithm that helps design user interfaces. 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. Result from our preliminary study involving three users indicates 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 and make it easier for end-users to further customize their interface without programming knowledge. I