Switched mode feedback control laws for nonholonomic systems in extended power form
Systems & Control Letters
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Knowledge Representation in Fuzzy Logic
IEEE Transactions on Knowledge and Data Engineering
The self-organizing relationship (SOR) network employing fuzzy inference based heuristic evaluation
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
IEEE Transactions on Computers
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Since the SOM visualizes the similarity of raw information on the competitive layer, it can be utilized in the field of pattern classification, data analysis, and so on. However, it cannot model the input-output characteristics of the system of interest. In order to squeeze out the input-output relationship from the data set with evaluation obtained by trial and error, the novel modeling tool was developed by the author (1999), which is the extension of SOM and in which the input-output relationship of the system is mapped onto the competitive layer. The system is named as self-organizing relationship network (SOR network). A set of units on the competitive layer of the SOR network after learning exhibits a set of typical input-output characteristics of the system of interest and thus the network achieves the knowledge acquisition (IF-THEN rules) from the raw data with evaluation and the effective fuzzy inference with defuzzification. The plenary talk presents the tutorial aspects of the SOR network and an application to an intelligent control.