Towards creative evolutionary systems with interactive genetic algorithm

Evolutionary computation has shown a great potential to work out several real-world problems in the point of optimization, but it is still quite far from realizing a system of matching the human performance. Especially, in creative applications such as architecture, art, music, and design, it is difficult to evaluate the fitness because the measure depends mainly on the human mind. To overcome this shortcoming, this paper presents a novel technique, called interactive genetic algorithm (IGA), which performs optimization with human evaluation and the user can obtain what he has in mind through repeated interaction with. To show the usefulness of the IGA to develop effective human-oriented evolutionary systems, we have applied it to the problems of fashion design and emotion-based image retrieval. Experiments with several human subjects indicate that the IGA approach is promising to develop creative evolutionary systems.