title: The Self-Organizing Relationship (SOR) network employing fuzzy inference based heuristic evaluation.
abstract: When human beings acquire a new skill, this usually is accomplished by the summarization of numerous experiences based on their own evaluation criteria. Usually these experiences are obtained by trial and error. The criteria for success and failure are based on our own knowledge or advice given by others. The Self-Organizing Relationship (SOR) network has been inspired by this process and has been proposed to emulate this process computationally. In the previous applications of the SOR network for controller design, the evaluation criteria have been assigned by using mathematical expressions. Generally, however, mathematical expressions of the evaluation criteria become difficult as the complexity of a target system increases. On the other hand, human beings can contrive to express their knowledge for evaluation by using heuristic expressions, although a target system is complicated. In this study, we employ fuzzy inference in order to realize heuristic expressions of the evaluation criteria.
authors.affiliation: Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu-ku, Kitakyushu, 8080196, Japan.
authors.forename: Takanori
authors.initials: T
authors.lastname: Koga
authors.forename: Keiichi
authors.initials: K
authors.lastname: Horio
authors.forename: Takeshi
authors.initials: T
authors.lastname: Yamakawa
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005069:Evaluation Studies as Topic; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated