Symbolic AI

Symbolic AI is an approach to artificial intelligence using human-readable symbols and logical rules to represent knowledge and solve problems. Also known as good old-fashioned AI (GOFAI) relies on explicit rules, ontologies, and reasoning engines to simulate intelligent behavior. In symbolic AI, concepts are represented through symbols (like words or objects), and relationships between them are defined through structured logic, often using methods like propositional logic or first-order predicate logic. Symbolic AI excels in domains where rules and logic are well-understood, such as mathematics, legal reasoning, or expert systems in medicine and finance. However, it struggles with ambiguity, unstructured data, and learning from experience, areas where machine learning and neural networks thrive.