Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes

In traditional epistemic logic—particularly modal logic—agents are often assumed to have complete and certain knowledge, which is unrealistic in real-world scenarios where uncertainty, imprecision, and the incompleteness of information are common. This study proposes an extension of the logic of dox...

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Main Authors: Jinjin Zhang, Xiaoxia Zhou, Yan Zhang, Lixing Tan
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Mathematics
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Online Access:https://www.mdpi.com/2227-7390/13/7/1105
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author Jinjin Zhang
Xiaoxia Zhou
Yan Zhang
Lixing Tan
author_facet Jinjin Zhang
Xiaoxia Zhou
Yan Zhang
Lixing Tan
author_sort Jinjin Zhang
collection DOAJ
description In traditional epistemic logic—particularly modal logic—agents are often assumed to have complete and certain knowledge, which is unrealistic in real-world scenarios where uncertainty, imprecision, and the incompleteness of information are common. This study proposes an extension of the logic of doxastic attitudes to a fuzzy setting, representing beliefs or knowledge as continuous values in the interval [0, 1] rather than binary Boolean values. This approach offers a more nuanced and realistic modeling of belief states, capturing the inherent uncertainty and vagueness in human reasoning. We introduce a set of axioms for the fuzzy logic of doxastic attitudes, formalizing how agents reason with regard to uncertain beliefs. The theoretical foundations of this logic are established through proofs of soundness and completeness. To demonstrate practical utility, we present a concrete example, illustrating how the fuzzy logic of doxastic attitudes can model uncertain preferences and beliefs.
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spelling doaj-art-638c2b389ebb4762af41292d6b9de3d62025-08-20T03:08:55ZengMDPI AGMathematics2227-73902025-03-01137110510.3390/math13071105Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic AttitudesJinjin Zhang0Xiaoxia Zhou1Yan Zhang2Lixing Tan3Department of Computer Science, Nanjing Audit University, Nanjing 211815, ChinaDepartment of Computer Science, Nanjing Audit University, Nanjing 211815, ChinaCollege of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Information Engineering, Taizhou University, Taizhou 225300, ChinaIn traditional epistemic logic—particularly modal logic—agents are often assumed to have complete and certain knowledge, which is unrealistic in real-world scenarios where uncertainty, imprecision, and the incompleteness of information are common. This study proposes an extension of the logic of doxastic attitudes to a fuzzy setting, representing beliefs or knowledge as continuous values in the interval [0, 1] rather than binary Boolean values. This approach offers a more nuanced and realistic modeling of belief states, capturing the inherent uncertainty and vagueness in human reasoning. We introduce a set of axioms for the fuzzy logic of doxastic attitudes, formalizing how agents reason with regard to uncertain beliefs. The theoretical foundations of this logic are established through proofs of soundness and completeness. To demonstrate practical utility, we present a concrete example, illustrating how the fuzzy logic of doxastic attitudes can model uncertain preferences and beliefs.https://www.mdpi.com/2227-7390/13/7/1105epistemic logiclogic of doxastic attitudesfuzzy logicsoundnesscompleteness
spellingShingle Jinjin Zhang
Xiaoxia Zhou
Yan Zhang
Lixing Tan
Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
Mathematics
epistemic logic
logic of doxastic attitudes
fuzzy logic
soundness
completeness
title Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
title_full Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
title_fullStr Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
title_full_unstemmed Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
title_short Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
title_sort fuzzy epistemic logic fuzzy logic of doxastic attitudes
topic epistemic logic
logic of doxastic attitudes
fuzzy logic
soundness
completeness
url https://www.mdpi.com/2227-7390/13/7/1105
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