Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
Computational Intelligence: Imitating Life
Computational Intelligence: Imitating Life
Soft Computing - A Fusion of Foundations, Methodologies and Applications
| Hi-index | 0.00 |
Recently, human-friendly support systems for product design have been developed as demands of individual user to products become diversified. In the previous works, Interactive Evolutionary Computation has been applied to support product designs. An advantage of Interactive Evolutionary Computation is that it can perform the optimization based on human preference and feeling in addition to the evaluation by fitness functions. However, the main target of the application of Interactive Evolutionary Computation lies in the design of appearance, not functionality. The simultaneous optimization of appearance and functions of a target product is very important to shorten the cycle of product development. Therefore, in this study, the final aim is to develop a support system for simultaneous design of appearance, shape, and functionality. First of all, in this paper, we focus on the development of a design system based on the user's preference. We apply Interactive Evolutionary Computation to make designs based on the human preference and feeling. As an example, we apply a proposed method to design a partner robot because the systematic tools of developing robots for daily use have rarely been developed. This system aims not to make final design but to make "Relation between the user and the robot." Next, we focus on the development of a simulation system to confirm the results of the developed. We can see images of the robot and movements, etc. by using this system, even if we do not actually make robots. Finally, we discuss the effectiveness of the proposed methods and future works.