The effect of user interaction mechanisms in multi-objective IGA

Authors:
Alexandra Melike Brintrup;Hideyuki Takagi
Affiliations:
Institute for Manufacturing;Faculty of Design
Venue:
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Year:
2007

Citing 2
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An input method using discrete fitness values for interactive GA

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Abstract

In this paper four mechanisms, fine and coarse grained fitness rating, linguistic evaluation and active user intervention are compared for use in the multi-objective IGA. The interaction mechanisms are tested on the ergonomic chair design problem. The active user intervention mechanism provided the best fitness convergence but resulted in the least diverse results. The fine grained evaluation provided a good blend of fitness convergence and diversity while the popular coarse grained discrete rating provided poor results. Linguistic evaluation resulted in poor qualitative fitness despite its fast speed of evaluation. The significant differences between interaction mechanisms show the need for further research.