Evolving interface designs to minimize user task times as simulated in a cognitive architecture

We present a novel approach to User Interface optimization. A Genetic Algorithm is used to evolve an interface layout to minimize user task times. Solutions are evaluated using the cognitive architecture - Active Control of Thought - Rational (ACT-R) to simulate the human cognition and motor action required to complete the task. A development environment, TOISE, has been created to integrate the GALib toolkit with user task definition and ACT-R. Our approach is tested on a classic design problem - the telephone keypad - in comparison with a Local Search. Solutions produced are also compared to the classic Bell telephone keypad. Our results show that both GA and LS evolve competitive solutions to the problem, with GA significantly outperforming LS. One of the solutions produced by GA approximates the classic Bell keypad. We conclude that the combination of EC and cognitive modeling may offer a competitive and cost effective alternative to interface design approaches driven by human evaluation.