Fuzzy Causal Inferences based on Fuzzy Semantics of Fuzzy Concepts in Cognitive Computing

Fuzzy semantics comprehension and fuzzy inference are two of the central abilities of human brains that play a crucial role in thinking, perception, and problem solving. A formal methodology for rigorously describing and manipulating fuzzy semantics and fuzzy concepts is sought for bridging the gap between humans and cognitive fuzzy systems. A mathematical model of fuzzy concepts is created based on concept algebra as the basic unit of fuzzy semantics for denoting languages entities in semantic analyses. The semantic operations of fuzzy modifiers and qualifiers on fuzzy concepts are introduced to deal with complex fuzzy concepts. On the basis the fuzzy semantic models, fuzzy causations and fuzzy causal inferences are formally elaborated by algebraic operations. The denotational mathematical structure of fuzzy semantics and fuzzy inferences not only explains the fuzzy nature of linguistic semantics and its comprehension, but also enables cognitive machines and fuzzy systems to mimic the human fuzzy inference mechanisms in cognitive informatics, cognitive linguistics, cognitive computing, and computational intelligence. Key-Words: Fuzzy systems, fuzzy semantics, fuzzy concept, fuzzy semantics, fuzzy inference, cognitive linguistics, cognitive informatics, cognitive computing, soft computing, computational intelligence.