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Can you explain Expert Systems in AI, including components and limitations?

Could you provide a detailed explanation of Expert Systems in AI, outlining their core architectural components and discussing their principal limitations?

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By Bharat Answered 4 months ago

Expert Systems are early AI programs that emulate human expert decision-making in a specific domain (e.g., medical diagnosis). Components: A knowledge base (facts/rules from experts), an inference engine (applies rules to data), and a user interface. Examples: MYCIN (diagnosed infections), DENDRAL (chemical analysis). Advantages: Consistent, explainable, and permanently available. Limitations: Brittleness (fail with unknown scenarios), high knowledge acquisition bottleneck (difficult to codify expertise), and inability to learn autonomously or handle commonsense reasoning, leading to their supplementation by modern machine learning.

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