Fuzzy Logic and Set Theory in Artificial Intelligence Decision-Making

Artificial Intelligence (AI) systems require the ability to make decisions under uncertainty and imprecision, which are common in real-world scenarios. Traditional methods struggle to handle such vagueness. Fuzzy Set Theory and Fuzzy Logic, introduced by Lotfi Zadeh, provide a framework for dealing with these issues. This paper explores how fuzzy systems enhance decision-making in AI, offering theoretical insights, practical applications, mathematical formulations, and the integration of fuzzy systems with other AI models. It also discusses the challenges and future directions in this research area.