Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
A framework for linguistic modelling
Artificial Intelligence
Modelling and Reasoning with Vague Concepts (Studies in Computational Intelligence)
Modelling and Reasoning with Vague Concepts (Studies in Computational Intelligence)
An introduction to bipolar representations of information and preference
International Journal of Intelligent Systems
Linguistic modelling based on semantic similarity relation among linguistic labels
Fuzzy Sets and Systems
A bipolar model of assertability and belief
International Journal of Approximate Reasoning
Imprecise bipolar belief measures based on partial knowledge from agent dialogues
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
A bipolar model of vague concepts based on random set and prototype theory
International Journal of Approximate Reasoning
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A generalised version of the label semantics framework is proposed as an epistemic model of the uncertainty associated with vague description labels. In this framework communicating agents make explicit decisions both about which labels are appropriate to describe an element x *** *** (the underlying universe), and also about which negated labels are appropriate to describe x . It is shown that such a framework can capture a number of different calculi for reasoning with vague concepts as special cases. In particular, different uncertainty assumptions are shown to result in the truth-functional max-min calculus and the standard label semantics calculus.