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Artificial Intelligence, Mathematics, and computer science depend heavily on logic for decision-making, knowledge representation, and automated reasoning. Perhaps the most powerful logical system in all three fields is First-Order Predicate Logic (FOPL). While propositional logic is not able to make very precise statements about objects and relationships, FOPL can. In this blog, we will explore the foundations, structure, and application of First-Order Predicate Logic, along with its syntax, semantics, and real-world relevance. Learn more about the foundation of logical reasoning in AI by reading our post on Propositional Logic. What is First-Order Predicate Logic? First-Order Predicate Logic (FOPL), or First-Order Logic (FOL), is a symbolic formal system that extends propositional logic by introducing quantifiers, predicates, functions, and variables. FOPL enables us to make statements like: ‘Each student has a laptop.’ This is more pr...

Propositional Logic Artificial Intelligence (AI) uses formal logic systems to mimic human reasoning. Of these systems, Propositional Logic is one of the pillars of knowledge representation and reasoning. Although it’s a basic and well-defined type of logic, it provides an entrance point for grasping more sophisticated logical frameworks in AI, such as First-Order Logic, Description Logic, and so forth. This blog post discusses propositional logic’s syntax, semantics, proof systems, resolution, Horn clauses, computability, and complexity, and its applications are limited in AI. What is Propositional Logic? Propositional logic, also referred to as propositional calculus or sentential logic, is concerned with propositions, i.e., declarative sentences that are true or false but not both. It does not include variables and quantifiers, unlike predicate logic. Propositional logic, in the case of AI, is applied to represent basic knowledge and deduce new facts based on current facts with the a...