Kumara Sastry

Combating user fatigue in iGAs: Partial ordering, support vector machines, and synthetic fitness

Llorà, X., Sastry, K., Goldberg, D. E., Gupta, A., Lakshmi, L. (2005). Proceedings of the Genetic and Evolutionary Computation Conference. 1363—1370. [Full paper - PDF] [Full paper - PS] [Presentation slides].

Abstract:
One of the daunting challenges of interactive genetic algorithms (iGAs)—genetic algorithms in which fitness measure of a solution is provided by a human rather than by a fitness function, model, or computation—is user fatigue which leads to sub-optimal solutions. This paper proposes a method to combat user fatigue by augmenting user evaluations with a synthetic fitness function. The proposed method combines partial ordering concepts, notion of non-domination from multiobjective optimization, and support vector machines to synthesize a fitness model based on user evaluation. The proposed method is used in an iGA on a simple test problem and the results demonstrate that the method actively combats user fatigue by requiring 3—7 times less user evaluation when compared to a simple iGA.

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