Representation and Reasoning of Fuzzy Knowledge Under Variable Fuzzy Criterion Using Extended Fuzzy Petri Nets

Fuzzy knowledge representation and reasoning is one of the key research subjects of artificial intelligence with uncertainty. Currently, fuzzy Petri nets (FPNs) cannot describe fuzzy nondeterministic knowledge based on the variable fuzzy criterion clearly. To solve this problem, we present an extend...

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Published inIEEE transactions on fuzzy systems Vol. 28; no. 12; pp. 3376 - 3390
Main Authors Zhou, Ruqi, Feng, Jiali, Chen, Yiqun, Chang, Huiyou, Zhou, Yuepeng
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptation models
Artificial intelligence
Cognition
Criteria
Education
Fuzzy knowledge representation and reasoning
Fuzzy logic
fuzzy Petri nets (FPNs)
Granular materials
Heuristic algorithms
Knowledge representation
Mapping
Petri nets
Qualitative analysis
qualitative criterion transformation
qualitative mapping
Reasoning
Transformations (mathematics)
Uncertainty
variable fuzzy criterion
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Abstract Fuzzy knowledge representation and reasoning is one of the key research subjects of artificial intelligence with uncertainty. Currently, fuzzy Petri nets (FPNs) cannot describe fuzzy nondeterministic knowledge based on the variable fuzzy criterion clearly. To solve this problem, we present an extended FPN model based on the qualitative mapping and the qualitative criterion transformation. First, the mechanism and the principles of the variable fuzzy criterion under qualitative mapping are introduced. The important theoretical basis of qualitative mapping is detection and integration of perceptual attribute features. Under transition degree function and the qualitative criterion transformation, the qualitative mapping better reflects the cases in which the fuzzy membership criterion is variable. Second, we use the characteristics of the qualitative mapping to propose a structure of attribute fuzzy information granule. Based on the logic operation of fuzzy information granule, we redescribe the four fuzzy production rules which are commonly used, and obtain four kinds of fuzzy qualitative judgment rules. They can explicitly express the occurrence process of transition nodes of FPNs, which strengthens the uncertain knowledge representation ability of FPNs. The new method makes it easy to construct a learning mechanism based on cognition in FPNs.
AbstractList Fuzzy knowledge representation and reasoning is one of the key research subjects of artificial intelligence with uncertainty. Currently, fuzzy Petri nets (FPNs) cannot describe fuzzy nondeterministic knowledge based on the variable fuzzy criterion clearly. To solve this problem, we present an extended FPN model based on the qualitative mapping and the qualitative criterion transformation. First, the mechanism and the principles of the variable fuzzy criterion under qualitative mapping are introduced. The important theoretical basis of qualitative mapping is detection and integration of perceptual attribute features. Under transition degree function and the qualitative criterion transformation, the qualitative mapping better reflects the cases in which the fuzzy membership criterion is variable. Second, we use the characteristics of the qualitative mapping to propose a structure of attribute fuzzy information granule. Based on the logic operation of fuzzy information granule, we redescribe the four fuzzy production rules which are commonly used, and obtain four kinds of fuzzy qualitative judgment rules. They can explicitly express the occurrence process of transition nodes of FPNs, which strengthens the uncertain knowledge representation ability of FPNs. The new method makes it easy to construct a learning mechanism based on cognition in FPNs.
Author Zhou, Ruqi
Chang, Huiyou
Zhou, Yuepeng
Chen, Yiqun
Feng, Jiali
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Snippet Fuzzy knowledge representation and reasoning is one of the key research subjects of artificial intelligence with uncertainty. Currently, fuzzy Petri nets...
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SubjectTerms Adaptation models
Artificial intelligence
Cognition
Criteria
Education
Fuzzy knowledge representation and reasoning
Fuzzy logic
fuzzy Petri nets (FPNs)
Granular materials
Heuristic algorithms
Knowledge representation
Mapping
Petri nets
Qualitative analysis
qualitative criterion transformation
qualitative mapping
Reasoning
Transformations (mathematics)
Uncertainty
variable fuzzy criterion
Title Representation and Reasoning of Fuzzy Knowledge Under Variable Fuzzy Criterion Using Extended Fuzzy Petri Nets
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