Quantification of “novelty” based on free-energy principle and its application for “aesthetic liking” for industrial products

Existing generative design cannot evaluate the perceived “aesthetic liking”. Hence, quantification method of aesthetic liking, which can be modelled by the summation of “complexity” and “novelty”, is needed. This study proposed the Gaussian curvature KL divergence as an index of novelty. This index represents the difference between a typical shape and a target shape on the basis of the free-energy principle. To confirm the effectiveness of the proposed index, we conducted cognitive experiments for shapes of an automobile generated by particle swarm optimization method with the proposed index as the objective function. The coefficient of determination between the proposed index and sensory evaluation values of “difference” were very high which support the applicability of the index (R2=0.86\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^{2} = 0.86$$\end{document}). By the summation of this index and a complexity index, a free-energy index is proposed, and its application for aesthetic liking is discussed. Finally, we confirmed that the Gaussian curvature KL divergence can be applied to evaluation of aesthetic liking.