Toward a Perception-Based Theory of Probabilistic Reasoning

By Lotfi A. Zadeh. Rough Sets and Current Trends in Computing, 2000

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Is there a need for fuzzy logic? (2008, background): “It should be pointed out that in the case of probability distributions it is necessary to differentiate between granular probability distributions and granule-valued probability distributions [102,107] (Fig.”
Uncertainty in big data analytics: survey, opportunities, and challenges (2019, background): “Fuzzy logic then handles the uncertainty associated with human perception by creating an approximate reasoning mechanism [41, 42].”
Toward a generalized theory of uncertainty (GTU) - an outline (2005, background): “Given these facts, how can we precisiate the meaning p? A key idea which underlies the concept of Precisiated Natural Language (PNL), Zadeh [55] is to represent the meaning of p as a generalized constraint, Fig.”
Toward a generalized theory of uncertainty (GTU)--an outline (2005, background): “More specifically, a given information, e.g., ‘‘Most Swedes are tall,’’ is perception-based and imprecise, Fig. 2. One of the basic limitations of standard probability theory, PT, is rooted in the fact that its conceptual structure does not accommodate perception-based information which is imprecise”