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Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes

Author

Listed:
  • Jinjin Zhang

    (Department of Computer Science, Nanjing Audit University, Nanjing 211815, China)

  • Xiaoxia Zhou

    (Department of Computer Science, Nanjing Audit University, Nanjing 211815, China)

  • Yan Zhang

    (College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China)

  • Lixing Tan

    (College of Information Engineering, Taizhou University, Taizhou 225300, China)

Abstract

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.

Suggested Citation

  • Jinjin Zhang & Xiaoxia Zhou & Yan Zhang & Lixing Tan, 2025. "Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes," Mathematics, MDPI, vol. 13(7), pages 1-14, March.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1105-:d:1622157
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    References listed on IDEAS

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    1. Gabriel Marín Díaz & Raquel Gómez Medina & José Alberto Aijón Jiménez, 2024. "Integrating Fuzzy C-Means Clustering and Explainable AI for Robust Galaxy Classification," Mathematics, MDPI, vol. 12(18), pages 1-27, September.
    2. Francisco Rodrigues Lima-Junior, 2024. "Advances in Fuzzy Logic and Artificial Neural Networks," Mathematics, MDPI, vol. 12(24), pages 1-3, December.
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