Upside-Down Logic in Double-Valued and Multi-Valued Plithogenic Fuzzy Sets: Toward Handling Two or More Contradiction Values

In the real world, many reversal phenomena occur, such as cases where a statement once regarded as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phenomena within a logical system. It inverts the truth and falsity of propositions through contextual transformations, thereby capturing ambiguity and reversals in reasoning processes. A Plithogenic Set models elements by means of attribute-based membership and contradiction functions, extending the classical frameworks of fuzzy, intuitionistic, and neutrosophic sets. The essential difference between Plithogenic Sets and traditional Fuzzy Sets lies in their ability to incorporate contradiction parameters, which naturally arise when uncertainty is transformed into certainty. While most studies assume that only a single contradiction parameter exists, this paper investigates how to handle situations where two or more contradiction values are present, in conjunction with the principles of Upside-Down Logic. Furthermore, we also examine methods for eliminating contradictions altogether.

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Publication Details

Published
2025-09-12
DOI
https://doi.org/10.31224/5360
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

Upside-Down Logic in Double-Valued and Multi-Valued Plithogenic Fuzzy Sets: Toward Handling Two or More Contradiction Values

Takaaki Fujita
Multi-Criteria Decision Making
article

Upside-Down Logic in Double-Valued and Multi-Valued Plithogenic Fuzzy Sets: Toward Handling Two or More Contradiction Values

Takaaki Fujita
article en

Abstract

In the real world, many reversal phenomena occur, such as cases where a statement once regarded as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phenomena within a logical system. It inverts the truth and falsity of propositions through contextual transformations, thereby capturing ambiguity and reversals in reasoning processes. A Plithogenic Set models elements by means of attribute-based membership and contradiction functions, extending the classical frameworks of fuzzy, intuitionistic, and neutrosophic sets. The essential difference between Plithogenic Sets and traditional Fuzzy Sets lies in their ability to incorporate contradiction parameters, which naturally arise when uncertainty is transformed into certainty. While most studies assume that only a single contradiction parameter exists, this paper investigates how to handle situations where two or more contradiction values are present, in conjunction with the principles of Upside-Down Logic. Furthermore, we also examine methods for eliminating contradictions altogether.

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Multi-Criteria Decision Making
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