FuzzyShell: a large-scale expert system shell using fuzzy logic for uncertainty reasoning

• Published in: IEEE transactions on fuzzy systems Vol. 6; no. 4; pp. 563 - 581
• Main Authors: Pan, J., Desouza, G.N., Kak, A.C.
• Format: Journal Article
• Language: English
• Published: IEEE 01.11.1998
• Subjects: Control systems; Engines; Expert systems; Fuzzy logic; Fuzzy reasoning; Humans; Hybrid intelligent systems; Large-scale systems; Robot vision systems; Uncertainty
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/91.728455

There exist in the literature today many contributions dealing with the incorporation of fuzzy logic in expert systems. However, unfortunately, much of what has been proposed can only be applied to small-scale expert systems; that is, when the number of rules is in the dozens as opposed to in the hundreds. The more traditional (nonfuzzy) expert systems are able to cope with large numbers of rules by using Rete networks for maintaining matches of all the rules and all the facts. (A Rete network obviates the need to match the rules with the facts on every cycle of the inference engine.) In this paper, we present a more general Rete network that is particularly suitable for reasoning with fuzzy logic. The generalized Rete network consists of a cascade of three networks: the pattern network, the join network, and the evidence aggregation network. The first two layers are modified versions of similar layers for the traditional Rete networks and the last, the aggregation layer, is a new concept that allows fuzzy evidence to be aggregated when fuzzy inferences are made about the same fuzzy variable by different rules.