Fuzzy sets and applications
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Credibility discounting in the theory of approximate reasoning
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Ontological approach to development of computing with words based systems
International Journal of Approximate Reasoning
Comparing approximate reasoning and probabilistic reasoning using the Dempster--Shafer framework
International Journal of Approximate Reasoning
Linguistic modelling and information coarsening based on prototype theory and label semantics
International Journal of Approximate Reasoning
A granularity-based framework of deduction, induction, and abduction
International Journal of Approximate Reasoning
Generalized theory of uncertainty (GTU)-principal concepts and ideas
Computational Statistics & Data Analysis
Concepts and fuzzy sets: Misunderstandings, misconceptions, and oversights
International Journal of Approximate Reasoning
Toward a generalized theory of uncertainty (GTU)--an outline
Information Sciences: an International Journal
Granular computing applied to ontologies
International Journal of Approximate Reasoning
Towards linguistic descriptions of phenomena
International Journal of Approximate Reasoning
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We describe the basic ideas of the theory of approximate reasoning and indicate how it provides a framework for representing human sourced soft information. We discuss how to translate linguistic knowledge into formal representations using generalized constraints. We consider the inference process within the theory of approximate reasoning and introduce the entailment principle and describe its centrality to this inference process. Next we introduce the idea of doubly uncertain statements such as John's friend is young. In these statements there exists uncertainty both with respect to value of the age, young, and the object associated with the age, John's friend. We suggest a method for representing these complex statements and investigate the problem of making inferences about specific objects.