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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...

 Artificial Intelligence (AI) has made tremendous progress over the past decades, from rule-based systems to powerful machine learning systems. Along the way, Knowledge-Based Systems have led the way in embedding human knowledge into computer systems. Knowledge-based Systems try to mimic the decision-making powers of human experts, providing solutions across different fields, from healthcare to finance. Understanding Knowledge-Based Systems A knowledge-based system is a computer application that uses a knowledge-based regarding a particular subject to address complex problems. Unlike conventional programs that use a sequence of instructions, knowledge-based systems use a knowledge base and an inference engine to mimic human thought processes. Knowledge Base : It contains the domain-specific facts, rules, and heuristics. Inference Engine: Uses logical rules on the knowledge base to derive new information or make decisions. The structure enables a knowledge-bas...