First-Order Logic (FOL) in Artificial Intelligence (AI) is a formal system used to represent and reason about knowledge. It extends propositional logic variables, predicates, and functions, allowing for more expressive statements about objects and their relationships. FOL enables AI systems to model complex real world scenarios, perform automated reasoning, and derive conclusions based on logical inference. It is widely used in knowledge representation, expert systems, and natural language processing, making it a foundational tool for building intelligent agents.

Rules of Inference in Artificial Intelligence (AI) are logical principles that enable the derivation of new truths from existing knowledge, ensuring sound reasoning in automated systems. They help AI systems in theorem proving, automated reasoning, and decision-making by systematically deriving conclusions from a given set of premises. Effective use of these inference rules enhances the ability of AI to reason, solve problems, and make logical decisions in knowledge-based systems.

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