Description
Book SynopsisThe papers in this text discuss the theoretical background of fuzzy logic and the applications of fuzzy reasoning to the problems of artificial intelligence, robotics and expert systems. Some papers explore fuzzy approaches to modelling of decision-making situations under uncertainty.
Table of ContentsPart 1 Approximate reasoning and fuzzy logic: fuzzy logic acquisition in expert systems, A. Averkin; fuzzy local inference in fuzzy knowledge basis, H. Bandemer; fuzzy sets in approximate reasoning, D. Dubois; SAK - an expert system shell based on complete many-valued (fuzzy) logic, J. Ivanek and E. Sovjakova; fuzzy logic with linguistic quantifiers in inductive learning, J. Kacprzyk; ontology, semantic and syntax of fuzzy logic, L. Kohout; on the logical basis of approximate reasoning, V. Novak; pseudophysical logic in artificial intelligence, D. Psopelov; Bayesian and possibilistic productions rules in syllogistic reasoning, M. Roubens; a fuzzy chip for high-speed approximate reasoning, T. Yamakawa. Part 2 Decision-making: clustering in Banach speces, J. Bezdek; triangular norm-based measures and games, E.P. Klement; multimodel representation and management of uncertainty, G. Klir; an optimum concept for fuzzified linear programming based on exact penalty functions, M. Kovacs; linear dependence of fuzzy vectors, M. Mares; on the nature of intransitivity in human preferential judgement, K. Nakamura; vaguely interrelated coefficients in linear programming as bicriterial optimization problem, J. Ramik; FULP - a PC-supported procedure for solving multicriteria linear programming with fuzzy data, H. Rommelfanger. Part 3 Applications in physics: on the structure of fuzzy observables, R. Mesiar and A. Kolesarova; on a fuzzy approach to quantum mechanics, B. Riecan.
