The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
A theory of measurement in diagnosis from first principles
Artificial Intelligence
Deriving minimal conflict sets by CS-trees with mark set indiagnosis from first principles
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Diagnosing multiple intermittent failures using maximum likelihood estimation
Artificial Intelligence
A new strategy for automotive off-board diagnosis based on a meta-heuristic engine
Engineering Applications of Artificial Intelligence
A global modular framework for automotive diagnosis
Advanced Engineering Informatics
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Model-based diagnosis is one of the active branches of Artificial Intellgence. Conflict recognition, aiming at generating all minimal conflict sets (MCSs), and candidate generation, aiming at generating all minimal hitting sets (MHSs), are of the two important steps towards to the final diagnosis results. Firstly an SE-tree based algorithm (CSSE-tree) for deriving all MCSs is given. Then a concept of inverse SE-tree (ISE-tree) is put forward, and an ISE-tree based algorithm (CSISE-tree) for deriving all MCSs is presented as well. Considering the similarity of generation of all MCSs and all MHSs for the collection of all MCSs, a uniform framework for deriving all MCSs and MHSs is proposed, too. Experimental results show that our algorithms have better efficiency than others in some situations.