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

Pravin ManeDepartment of Management Studies, Bharati Vidyapeeth (Deemed to be University), Institute of Management and Entrepreneurship Development Pune, Pune, Maharashtra, 411038, IndiaDalwinder KaurSchool of Education, No. 3 Jalan Kia Peng, Manipal GlobalNxt University, Kuala Lumpur, 50450, MalaysiaSagarkumar S. BadhiyeDepartment of Computer Science and Engineering, Nagpur Campus, Symbiosis International (Deemed University), Symbiosis Institute of Technology, Nagpur, Maharashtra, 440008, IndiaArchana R. PanhalkarDepartment of Artificial Intelligence and Data Science, Amrutvahini College of Engineering, Sangamner, Maharashtra, 422608, IndiaSaurabh SaojiAnorgul AshirovaDepartment of General Professional Sciences, Mamun University, Khiva, 220900, Uzbekistan

2026en

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ABI

Annotatsiya

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.

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DOI: 10.47974/jim-2502

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