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An innovative quantum-fuzzy paradigm for time- and context-sensitive membership: Quantive logic
Mehmet Akif Yerlikaya1, Ömer Faruk Efe2, Burak Efe3
1Bitlis Eren University, Department of Mechanical Engineering, Bitlis, Turkiye.
Plos One
|July 30, 2026
Summary
Quantive Logic (QL) introduces a quantum-inspired fuzzy framework to model time- and context-sensitive decision-making. This approach enriches membership representation by capturing dynamic interactions between criteria, improving real-world problem-solving.
Area of Science:
- Decision Science
- Fuzzy Logic
- Quantum Computing
Background:
- Real-world uncertainty is dynamic, context-dependent, and involves multi-criteria interactions.
- Classical fuzzy logic struggles with temporal dynamics and isolated criterion treatment.
- Quantum-inspired models offer rich representations but lack integration with decision tasks.
Purpose of the Study:
- Propose Quantive Logic (QL), a quantum-inspired fuzzy framework.
- Enable time- and context-sensitive membership representation.
- Integrate dynamic interactions and contextual shifts into decision-making.
Main Methods:
- Represent elements as quantive membership states in a complex Hilbert space.
- Utilize projections for conventional fuzzy degrees.
- Employ phase and superposition to model interactions and context.
- Formalize initialization and update of states via linear operators for temporal/contextual shifts.
Main Results:
- QL recovers conventional fuzzy degrees through projections.
- Phase and superposition capture complex interactions and context effects.
- Demonstrated application in a credit-risk assessment scenario with dynamic economic conditions.
Conclusions:
- QL provides a complementary layer to existing models for enriched membership representation.
- Effectively refines risk judgments by incorporating interactions and scenario-dependent effects.
- Addresses limitations of classical fuzzy logic in dynamic, multi-criteria decision problems.
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