Fuzzy set theory in medical diagnosis
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Convex Optimization
Measuring inconsistency in knowledgebases
Journal of Intelligent Information Systems
Distance semantics for database repair
Annals of Mathematics and Artificial Intelligence
Quantifying information and contradiction in propositional logic through test actions
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
On the (fuzzy) logical content of CADIAG-2
Fuzzy Sets and Systems
Measuring inconsistency in probabilistic knowledge bases
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Measuring and repairing inconsistency in probabilistic knowledge bases
International Journal of Approximate Reasoning
A probabilistic interpretation of the medical expert system CADIAG-2
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Intelligent Systems, Design and Applications (ISDA 2009)
Approaches to measuring inconsistent information
Inconsistency Tolerance
Artificial Intelligence in Medicine
The Consistency of the Medical Expert System CADIAG-2: A Probabilistic Approach
Journal of Information Technology Research
Distance-Based measures of inconsistency
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Consequence Relation for Graded Inference within the Frame of Infinite-valued Łukasiewicz Logic
Fundamenta Informaticae - MFCS & CSL 2010 Satellite Workshops: Selected Papers
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In this paper we present a family of measures aimed at determining the amount of inconsistency in knowledge bases with graded truth, i.e., knowledge bases that consist of propositions along with a degree of truth or an interval of possible degrees of truth. Our approach to measuring inconsistency is also graded in the sense that we consider minimal adjustments in the truth degrees of the propositions necessary to make the knowledge base consistent within the frame of Lukasiewicz semantics. The computation of the family of measures we present here, in as much as it yields an adjustment in the truth degrees of each proposition that restores or brings consistency, provides the modeler with possible repairs of the knowledge base. Our motivation and case study for this paper is the fuzzy medical expert system CADIAG2.