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Open Access ·Peer-reviewed·ISSN (Online): 2169-012X·ISSN (Print): 0972-0502

Freq.: MONTHLY - Publishes the methodological and theoretical role of mathematics and mathematical applications underpinning scientific research.

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Open Access Research Article

Set theory and logic-driven AI reasoning for decision-making systems

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pp. 671–679Vol. 29Issue 3March 2026DOI: 10.47974/JIM-2502XML
Received:
01 Apr 2025
Published Online:
18 Mar 2026
Article type:
Research Article
Language:
EN
Article no.:
JIM-2502
Pages:
671–679

Abstract

In the systems making decisions, this paper examines the ability of set theory and logic to be combined as building blocks to AI-driven thinking. It is revealed that modeling any complex decision problem become clear and structured through the formalization of the knowledge representation by sets and logical formulae. Application of propositional and predicate logic allows strong reasoning processes to arrive at good results and assist individuals to make good decisions. In this case we demonstrate how to construct decision-making systems in a manner that represents them as logical and set-based structures. This approach offers a systematic and scientifically valid approach to the development of decision-support systems that are effective, easy to comprehend, and straightforward.

Keywords

Subject Classifications

03E0503E75

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