DocumentCode :
2610526
Title :
An improved critical diagnosis reasoning method
Author :
Xu, Yue ; Zhang, Chengqi
Author_Institution :
Dept. of Math. Stat. & Comput. Sci., New England Univ., Armidale, NSW, Australia
fYear :
1996
fDate :
16-19 Nov. 1996
Firstpage :
170
Lastpage :
173
Abstract :
Model-based diagnosis has the disadvantage of a high computational complexity. One way to overcome this disadvantage is to focus the diagnosis on a reduced diagnostic space. We propose an improved critical diagnosis reasoning method based on the method proposed by (Raiman et al., 1993). The method focuses the diagnosis on finding out the kernel diagnoses instead of the whole diagnoses. We give an updated definition of critical cover which we call "critical partition". The conditions satisfied by critical partition are relaxed compared with the conditions for critical cover. Correspondingly, a non-backtracking algorithm called Searching Critical Partition (SCP) to find out the critical partition is also proposed.
Keywords :
computational complexity; diagnostic expert systems; diagnostic reasoning; model-based reasoning; search problems; Searching Critical Partition; computational complexity; critical cover; critical diagnosis reasoning method; critical partition; kernel diagnoses; model-based diagnosis; nonbacktracking algorithm; reduced diagnostic space; Artificial intelligence; Computational complexity; Computer architecture; Distributed computing; Fault diagnosis; Kernel; Mathematical model; Mathematics; Partitioning algorithms; Statistical distributions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 1996., Proceedings Eighth IEEE International Conference on
ISSN :
1082-3409
Print_ISBN :
0-8186-7686-7
Type :
conf
DOI :
10.1109/TAI.1996.560448
Filename :
560448
Link To Document :
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