Foundations of logic programming
Foundations of logic programming
A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Design of a fuzzy-logic based diagnostic model for technical processes
Fuzzy Sets and Systems
Cumulative default logic: finite characterization, algorithms, and complexity
Artificial Intelligence
Artificial Intelligence
Abduction to plausible causes: an event-based model of belief update
Artificial Intelligence
Semantics and complexity of abduction from default theories
Artificial Intelligence
A New Diagnosis Approach by Deduction and Abduction
Proceedings of the International Workshop on Expert Systems in Engineering, Principles and Applications
Intelligent Student Profiling with Fuzzy Models
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 3 - Volume 3
Explanation and Prediction: An Architecture for Default and Abductive Reasoning
Explanation and Prediction: An Architecture for Default and Abductive Reasoning
Diagnosability of fuzzy discrete event systems
Information Sciences: an International Journal
Algorithms and application in decision-making for the finest splitting of a set of formulae
Knowledge-Based Systems
Fault diagnosis with dynamic fuzzy discrete event system approach
TAINN'05 Proceedings of the 14th Turkish conference on Artificial Intelligence and Neural Networks
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Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent eLearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e.g., the fault diagnosis of student behaviors in the eLearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, Fuzzy Diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the Fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world eLearning case is described to demonstrate the application of our diagnostic framework.