Graduate Seminar: Graded Logic for AI Applications

Abstract

Graded logic is a logic of natural human reasoning and decision-making. It is developed for AI applications in the area of decision-support systems. If we want that machines can make decisions in a way similar to humans, then we must first understand the properties of human natural logic reasoning. That is the goal of Graded logic. Human reasoning is observable, measurable, modellable, and explainable. Based on observations and experiments with human subjects, Graded Logic includes unique mathematical models of graded propositional calculus. That is the essential component of the LSP method for evaluation, optimization, comparison and selection of complex objects and alternatives. Based on this methodology  we present applications in computational intelligence, in several decision-making areas, and discuss opportunities for further research, development, and industrial applications.

Biography of Speaker

Jozo Dujmović received the Dipl. Ing. degree in electronic and telecommunication engineering, and the M.Sc. and Sc.D. degrees in computer engineering, all from the University of Belgrade, Serbia. Since 1994 he has been Professor of Computer Science at San Francisco State University, where he served as Chair of Computer Science Department from 1998 to 2002. His permanent research interest is in logic foundations of soft computing and in decision support systems. In 1973 he introduced the graded logic concepts of andness and orness and graded logic aggregators based on continuous transition from conjunction to disjunction. He used these concepts to develop the Logic Scoring of Preference (LSP) method for evaluation, selection, and optimization of complex systems, as well as the complete LSP decision support software. He is the author of more than 190 refereed publications, a Life Senior Member of IEEE, and the recipient of NAFIPS, CMG, Informatica, and ETAN best paper awards. His most recent book Soft Computing Evaluation Logic was published by Wiley and IEEE Press in 2018. His industrial experience includes R&D work in the Institute “M. Pupin” in Belgrade, and consulting in the areas of soft computing decision methods, performance evaluation, and software design. He is a founder and principal of SEAS (seas.com), a company specializing in soft computing decision methods and software support for the LSP method.