Presentation slides (in PDF)

Graded Logic (GL) is a human-centric continuum-valued propositional logic. It is based on observing, measuring, modeling, and explaining natural human reasoning with graded (continuum-valued) percepts. GL is fully continuum-valued: it uses continuum-valued logic variables, continuum-valued simultaneity (graded conjunction), continuum-valued substitutability (graded disjunction), and continuum-valued importance of logic variables. To adjust properties of graded conjunction and graded disjunction, GL introduced an adjustable conjunction degree (andness), and an adjustable disjunction degree (orness). The graded conjunction and the graded disjunction are complementary and unified in a single continuum-valued, andness-directed, importance-weighted, and annihilator-selectable basic logic function called Graded Conjunction/Disjunction (GCD). GCD offers a parameterized continuous transition from the drastic conjunction (the model of ultimate simultaneity) to the drastic disjunction (the model of ultimate substitutability). The strict use of continuum-valued objects is a unique distinctive property introduced in Graded Logic. Based on that property, GL is a seamless generalization of the classical bivalent Boolean logic, fuzzy logic propositional calculus, and non-classical continuum-valued logics. Since GL is a basic component of quantitative models of human decision-making, it is also used as a central component of the Logic Scoring of Preference (LSP) method for professional evaluation and decision making. The goals of this talk are to summarize properties of GL and the LSP method, and to exemplify their use in professional decision making.

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. Before his current position with San Francisco State University, he was the Professor of computer science with the University of Belgrade; the University of Florida, Gainesville, FL, USA; the University of Texas, Dallas, TX, USA; and Worcester Polytechnic Institute, Worcester, MA, USA. In addition, he taught in graduate Computer Science programs with the National Universities of San Luis and Jujuy (both in Argentina). With the University of Belgrade School of Electrical Engineering, where he taught 24 years, he also served as the Chairman of the Computer Science Department and founding Director of the Belgrade University Computing Center.  

His primary 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, computer performance evaluation, and software design. In 1997, he founded System Evaluation & Selection (SEAS), a San Francisco-based company specializing in soft computing decision methods and their software support (seas.com). He currently serves as a Principal with SEAS.