An Extended G-Net Model for Knowledge Representation
Abstract
A new, generalized scheme for knowledge representation of fuzzy timed systems is proposed. The scheme is based on principles of a G-net model. We extended the existing G-net capabilities by the possibility of describing fuzzy defined and time dependent relationships among the system agents.
A fuzzy system is described by fuzzy relations. A fuzzy production rule is represented by a fuzzy term and valued by a certainty factor. Possibilities of modeling different types of knowledge are given.
Time dependencies in the systems and their representations vary according to the nature of the problems studied and a type of represented knowledge.
The represented scheme is capable of a static and a dynamic knowledge representation in a unique framework and enables interaction and coordination of both types of knowledge.
Finally, some illustrative examples are given.
A fuzzy system is described by fuzzy relations. A fuzzy production rule is represented by a fuzzy term and valued by a certainty factor. Possibilities of modeling different types of knowledge are given.
Time dependencies in the systems and their representations vary according to the nature of the problems studied and a type of represented knowledge.
The represented scheme is capable of a static and a dynamic knowledge representation in a unique framework and enables interaction and coordination of both types of knowledge.
Finally, some illustrative examples are given.
Keywords
G-net model, fuzzy production rule
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