Generalized Information Theory: Emerging Crossroads of Fuzziness and Probability

Abstract

Motivated primarily by some fundamental methodological issues emerging from the study of complex systems, a research program whose objective is to study uncertainty and uncertainty-based information in all their manifestations was introduced in the early 1990s under the name "generalized information theory" (GIT) [1]. In GIT, as in classical, probability-based information theory, uncertainty is the primary concept and information is defined in terms of uncertainty reduction. This restricted meaning of the concept of information is described in GIT by the qualified term "uncertainty-based information." In GIT, contrary to classical information theory, uncertainty is viewed as a broader concept than the concept of probability. The purpose of introducing GIT in this plenary lecture is to examine, within the conceptual framework of GIT, the distinct roles of probability and fuzziness in dealing with uncertainty.