Symbolic AI

Fundamentals

The classic approach to AI - encoding knowledge as explicit rules and logic instead of learning patterns from data.

Before machine learning took over, AI meant symbolic AI: humans writing down knowledge as facts and rules - if the patient has fever and rash, consider these diagnoses - and the computer reasoning over them with formal logic.Its strength is transparency: you can trace exactly why the system concluded what it did. Its weakness is brittleness - the real world rarely fits clean rules. It still runs expert systems, tax software, and planning tools, and it is returning in hybrid form alongside neural networks.