Rule-based reasoning and its role in intelligent decision making

Abstract

Rule-based reasoning represents a foundational approach to intelligent decision-making by applying structured logic through predefined rules. This article examines the theoretical basis and practical implementation of rule-based reasoning systems, highlighting their strengths in interpretability, consistency, and transparency. It also discusses the limitations of rule-based reasoning in managing uncertainty, scalability, and adaptability in dynamic environments. Through analysis of its applications in domains such as healthcare, law, and finance, the article explores how rule-based reasoning continues to serve critical roles despite the rise of data-driven models. Emphasis is placed on the integration of rule-based reasoning with other artificial intelligence techniques to create hybrid systems that balance explainability with flexibility. The discussion concludes with reflections on the enduring relevance of rule-based systems in the context of ethical and accountable artificial intelligence development.