Evolutionary Based Adaptive User Interfaces in Complex Supervisory Tasks
Gary G. Yen · IGI Global eBooks · 2010
In this chapter, the author proposes a novel idea based on evolutionary algorithm for adaptation of the user interface in complex supervisory tasks. Under the assumption that the user behavior is stationary and that the user has limited cognitive and motor abilities, the author has shown that a combination of genetic algorithm for constrained optimization and probabilistic modeling of the user may evolve the adaptive interface to the level of personalization. The non-parametric statistics has been employed to evaluate the feasibility of the ranking approach. The method proposed is flexible and easy to use in various problem domains. The author has tested the method with an automated user and a group of real users in an air traffic control environment. The automated user, implemented for initial tests, is built under the same assumptions as a real user. In the second step, the author has exploited the adaptive interface through a group of real users and collected subjective ratings using questionnaires. The author has shown that the proposed method can effectively improve human-computer interaction and his approach is pragmatically a valid design for the interface adaptation in complex environments.