The effect of user interaction mechanisms in multi-objective IGA
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
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LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
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This paper proposes a new input method for human operators of an interactive GA to reduce their psychological burden. This method utilizes discrete fitness values to reduce the psychological stress involved in the input procedure. The advantage and disadvantage of the proposed method are evaluated and discussed. We conducted simulations to investigate the influence of quantization noise stemming from the use of discrete fitness values on convergence. Results show that the quantization noise does not significantly worsen convergence in practical use. The proposed method and a variation of the method which combines both discrete and continuous fitness values are evaluated using two subjective tests involving the task of drawing faces. The results of the subjective tests indicate that our proposed method and its variation can significantly reduce the psychological stress level of human interactive GA operators. The experimental results of the proposed method are discussed on its universality.