Uncertain knowledge representation and reasoning with linguistic belief structures. (English) Zbl 1535.68390
Summary: In this paper, we extend the concept of Dempster-Shafer Belief Structures to the case of Linguistic Belief Structures, whose focal elements and probability mass assignments are linguistic, i.e. words modeled by Interval Type-2 Fuzzy Sets. We show that Linguistic Weighted Averages are pertinent tools for derivation of lower and upper probabilities from such Belief Structures, especially when words describing probability masses and focal elements are modeled by Interval Type-2 Fuzzy Sets synthesized by collecting data from subjects. We moreover introduce methods for performing operations on Linguistic Belief Structures as well as combining them. We demonstrate how Linguistic Belief Structures can be used to represent uncertainties in natural languages and present methods for inference from them.
MSC:
| 68T37 | Reasoning under uncertainty in the context of artificial intelligence |
| 68T30 | Knowledge representation |
Keywords:
combination of evidence; compatibility measures; computing with words; doubly normalized linguistic weighted averages; interval type-2 fuzzy sets; linguistic weighted averages; linguistic belief structures; lower probabilities; upper probabilitiesReferences:
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