DocumentCode :
2472878
Title :
Efficient reasoning for uncertainty management in expert systems
Author :
Guan, J.W. ; Bell, D.A.
Author_Institution :
Dept. of Inf. Syst., Ulster Univ., Jordanstown, UK
fYear :
1995
fDate :
20-23 Feb 1995
Firstpage :
333
Lastpage :
339
Abstract :
Bayesian statistics assigns basic probabilities to singletons. By assigning basic probabilities to subsets, the Dempster Shafer theory significantly generalizes Bayesian statistics to represent evidence and to develop evidential reasoning. But the computation of probabilities on subsets is exponentially complex. J.A. Barnett (1981) presented a linear time computational technique. G. Shafer and R. Logan (1987) gave an algorithm for the exact implementation of Dempster Shafer´s rule in the case of hierarchical evidence. Earlier, we improved the algorithm (for the second propagation) to make the algorithm more attractive for embodiment in working systems (J.W. Guan and D.A. Bell, 1991). The paper compliments that earlier paper by giving details and examples of our improved algorithm
Keywords :
Bayes methods; case-based reasoning; expert systems; probability; uncertainty handling; Bayesian statistics; Dempster Shafer theory; evidence; evidential reasoning; expert systems; hierarchical evidence; linear time computational technique; uncertainty management; Algorithms; Expert systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence for Applications, 1995. Proceedings., 11th Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
0-8186-7070-3
Type :
conf
DOI :
10.1109/CAIA.1995.378803
Filename :
378803
Link To Document :
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