We (1) propose a method for accelerating the convergence of interactive evolutionary computation (IEC) by incorporating multiple evaluation models of previous IEC users, (2) evaluate the method's performance according to the similarity metric of users' evaluation characteristics, and (3) investigate its practical usefulness by measuring users' evaluation characteristics for real-world applications on the metric. Although conventional IEC with a function learning the current IEC user's evaluation characteristics cannot use the evaluation characteristics until the model is learned, the proposed IEC uses models learned from previous users until the current user's behavior is learned. The model from a previous IEC user whose evaluation values are most similar to those of the current IEC user is selected and used instead of the current IEC user's model till the current user's model is leaned. The viability of this method is evaluated on similarity distance of evaluation characteristics with simulation, and the simulation results are compared with the real IEC user's evaluation characteristics for four different types of real applications. Through this evaluation, we obtain a rating method for predicting the effectiveness of the proposed acceleration method for different types of IEC applications.

SUMMARYIn conventional studies of facial caricature drawing, image processing of a face picture is performed, and feature points are extracted. A caricature is drawn based on these points. On the other hand, there have been few studies of facial caricature drawing based on impressions, which are subjective and dependent on the person who views the face. The purpose of this paper is to draw a facial caricature using linguistic expressions in order to reflect personal impressions of a face. Cheerfulness, gentleness, and so on are considered as impressions of a face. The drawn facial caricature can be modified by the use of linguistic terms. The concept of exaggeration, which is important for emphasis of personality in a caricature drawing, is also introduced by considering the line thickness and the exaggeration rate. Facial caricatures are evaluated by subjects who themselves draw them by the presented method, and also by other subjects, and the validity of the process is discussed

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