Uncertainty and RuleML Rulebases: A Preliminary Report

Uncertainty and RuleML Rulebases: A Preliminary Report

Uncertainty, like imprecision and vagueness, has gained considerable attention the last decade. To this extend we present a preliminary report on extending the Rule Markup Language (RuleML) with fuzzy set theory, in order to be able to represent and handle vague knowledge. We also provide semantics...

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Hauptverfasser: Stoilos, Giorgos, Stamou, Giorgos, Tzouvaras, Vassilis, Pan, Jeff Z.
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Applied sciences
Computer science
control theory
systems
Exact sciences and technology
Programming languages
Software
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Stamou, Giorgos
Tzouvaras, Vassilis
Pan, Jeff Z.
description Uncertainty, like imprecision and vagueness, has gained considerable attention the last decade. To this extend we present a preliminary report on extending the Rule Markup Language (RuleML) with fuzzy set theory, in order to be able to represent and handle vague knowledge. We also provide semantics for the case of fuzzy FOL RuleML.
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source Springer Books
subjects Applied sciences
Computer science
control theory
systems
Exact sciences and technology
Programming languages
Software
title Uncertainty and RuleML Rulebases: A Preliminary Report
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