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Expert Systems
Early AI systems (1970s–1990s)
Rule-based: encode human expert knowledge as if-then rules.
Precursor to modern ML, focused on symbolic reasoning rather than data-driven learning.
Pros
- Transparent and explainable (rules are visible).
- Effective in narrow, well-defined domains.
Cons
- Knowledge engineering is labor-intensive.
- Doesn’t scale well as rules explode.
- Cannot adapt automatically from new data.