NDLI: Techniques for the Fusion of Symbolic Rules in Distributed Organic Systems

Content Provider	IEEE Xplore Digital Library
Author	Buchtala, O. Sick, B.
Copyright Year	2006
Description	Author affiliation: Fac. of Comput. Sci. & Math., Passau Univ. (Buchtala, O.; Sick, B.)
Abstract	Humans do not only learn by their own experience but also by rules obtained from other humans. It is a challenging idea to enable distributed, intelligent computer systems to follow this human archetype. A basic technique needed for such an "organic" system is the fusion of functional knowledge in form of symbolic rules that are gained from several sources (nodes of the distributed system). We assume that these nodes are equipped with self-learning classifiers on the basis of a hybrid radial basis function network/fuzzy system paradigm. We provide methods for the fusion of fuzzy-type rules extracted from such classifiers. These methods aim at preserving the consistency and comprehensibility of a found rule set (e.g. low number of rules, distinguishability of membership functions) by means of a regularization approach
Starting Page	85
Ending Page	90
File Size	1587212
Page Count	6
File Format	PDF
ISBN	1424401666
DOI	10.1109/SMCALS.2006.250696
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Intelligent systems Neural networks Fuzzy systems Computer science Mathematics Distributed computing Radial basis function networks Application software Intrusion detection
Content Type	Text
Resource Type	Article

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