Professor Dr Hideyuki Takagi
Kyushu University, Japan
takagi@design.kyushu-u.ac.jp

Soft Computing Approaches to Knowledge Handling

We introduce (1) knowledge acquisition and knowledge compilation using fuzzy systems (FS), neural networks (NN), and evolutionary computation (EC), (2) interactive evolutionary computation (IEC) to optimize target systems based on IEC user's knowledge, experiences, and preferences together with a computer and (3) knowledge acquisition in human science by analyzing the target system optimized by an IEC user.

FS, NN, and EC are three major techniques of Soft Computing, and they has used to extracted explicit knowledge from data using FS+NN and FS+EC framework since late 1980's using explicit knowledge expressions of IF-THEN fuzzy logic rule structures and NN learning capability or EC optimization algorithms. Especially, this approach is effective when we have partial knowledge of the target data or systems; we express our partial a priori knowledge in IF-THEN fuzzy logic rules as a skeletal structure, and detail parts of the rules are adjusted using NN.

IEC is a cooperation framework of a human and a computer, and EC in a computer optimizes a target system based on human subjective evaluations which are further based on his/her knowledge, experiences, and preferences. When we can measure system performance, we can use classical optimization techniques without a human. However, there are many tasks that computer cannot measure how the target systems qre good or bad, such as hearing-aid fitting, design of robot's cute or funny motions, and others. In such cases, IEC provides a framework that we can embed our evaluations based on our knowledge, experiences, and preferences.

By analyzing the system optimized by an IEC user, we may be able to obtain his/her information that are a key of his/her IEC evaluations for the system. This is a new approach for human science. We show some examples of this approaches including measuring psychological dynamics of mental patients and obtaining new knowledge of hearing.

Biography of Professor Dr Hideyuki Takagi
Hideyuki TAKAGI received the degrees of Bachelor and Master from Kyushu Institute of Design in 1979 and 1981, and the degree of Doctor of Engineering from Toyohashi University of Technology in 1991. He was a researcher at Panasonic Central Research labs in 1981 - 1995, was an Associate Professor of Kyushu Institute of Design in 1995 - 2003, and is a Professor of Kyushu University now. He was a visiting researcher at UC Berkeley in 1991-1993 hosted by Prof. L. A. Zadeh.

He had worked on neuro-fuzzy systems in 1987 - early 1990's and extended his interests to fusing neuro-fuzzy-genetic algorithms and human factors. Now, he aims Humanized Computational Intelligence and is focusing on interactive evolutionary computation (IEC) as a tool for this research direction and developing methods for enhancing evolutionary computation. The number of citations of the most cited his IEC paper is around 1,500 times, and his well cited papers can be found at Google Scholar Citations.

He has been a volunteer for IEEE Systems, Man, and Cybernetics (SMC) Society. Some of his contributions are: Vice President in 2006 - 2009: a member of Administrative Committee/Board of Governors in 2001 - 2010, and 2016 - 2018: Chair of SMC Japan Chapter in 2014 - 2017 and a Vice-Chair in 2018 - 2019: Technical Committee (TC) Coordinator in 2004 - 2005: Chair of TC on Soft Computing in 1998 - 2004 and since 2008: Distinguished Lecturer in 2006 - 2011: Associate Editor of IEEE Transactions on SMC, Part B / Cybernetics since 2001.

See his further detail bio at his web page.