报 告 人：寺野隆雄，日本东京工业大学（Tokyo Institute of Technology）教授
报告题目：Learning Classifier System and Its Application to Extraction of Plant Operation
Knowledge from Time Series Data
内容简介：Learning Classifier System (LCS) is a yet another architecture for machine learning. LCS is characterized by rule-based problem solving, reinforcement learning, and evolutionary computation. Although the techniques are not well known in the literature, LCS has much potential for machine learning applications. In the presentation, I will introduce basic principles of LCS techniques, then discuss a data mining application system to extract plant operation knowledge from time series data of a biochemical process.
The system is a specific one, however, it is applicable to various task domains in complex data mining problems.
报告人简介：Takao TERANO is a professor at School of Computing, Tokyo Institute of Technology. He received BA degree in Mathematical Engineering in 1976 from University of Tokyo, M. A. degree in Information Engineering in 1978 from University of Tokyo, and Doctor of Engineering Degree in 1991 from Tokyo Institute of Technology.
His research interests include Agent-based Modeling, Knowledge Systems, Evolutionary Computation, and Service Science. He is a member of the editorial board of major Artificial Intelligence- and System science- related academic societies in Japan and a member of IEEE, AAAI, and ACM. He is also the president of PAAA.