Keynote Presentation
 

"Learning Methods for Evolving Intelligent Systems and Agents" By Dr. Ronald R. Yager, Machine Intelligence Institute, Iona College, New York

Abstract

In this presentation our concern is with technologies that allow the construction of intelligent systems agents that can evolve and learn based on experiences. We discuss a number of technologies that support this capability: the participatory learning paradigm, the hierarchical prioritized structure and the mountain clustering method. The basic premise of the participatory learning paradigm is that learning takes place in the framework of what is already learned and believed. The implication of this is that every aspect of the learning process is affected and guided by the current belief system. This name, participatory learning, highlights the fact that in learning we are in a situation in which the current knowledge of what we are trying to learn participates in the process of learning about itself. The hierarchical prioritized structure provides a generalization of fuzzy systems modeling by introducing a hierarchical representation of the rules. It supports systems evolution by allowing the learning of new rules based and their insertion at different levels of the hierarchy.

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Bio

Ronald R. Yager has worked in the area of machine intelligence for over twenty-five years. He has published over 500 papers and fifteen books in areas related to fuzzy sets, decision making under uncertainty and the fusion of information. He is among the world’s top 1% most highly cited researchers with over 7000 citations. He was the recipient of the IEEE Computational Intelligence Society Pioneer award in Fuzzy Systems. Dr. Yager is a fellow of the IEEE, the New York Academy of Sciences and the Fuzzy Systems Association. He was given a lifetime achievement award by the Polish Academy of Sciences for his contributions. He served at the National Science Foundation as program director in the Information Sciences program. He was a NASA/Stanford visiting fellow and a research associate at the University of California, Berkeley. He has been a lecturer at NATO Advanced Study Institutes. He has been a distinguished honorary professor at the Aalborg University Esbjerg Denmark. He is an affiliated distinguished researcher at the European Centre for Soft Computing. He received his undergraduate degree from the City College of New York and his Ph. D. from the Polytechnic University of New York. Currently, he is Director of the Machine Intelligence Institute and Professor of Information Systems at Iona College. He is editor and chief of the International Journal of Intelligent Systems. He serves on the editorial board of numerous technology journals including the IEEE Transactions on Fuzzy Systems, Neural Networks, General Systems, IEEE Intelligent Systems, Fuzzy Sets and Systems, the Journal of Approximate Reasoning and the Journal of Group Decision Making and Negotiations. Much of his work has been transitioned into commercial applications.

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