Review Expert System

An expert system is a program that applies encoded specialist knowledge and rules to solve problems in a narrow domain.

An expert system is a program that represents specialist knowledge, often as facts and rules, and applies an inference process to problems in a narrow domain.

Expert systems show an earlier path to AI: knowledge was explicitly encoded rather than learned from huge datasets. The comparison clarifies the strengths and maintenance burdens of rules, learned models, and hybrid systems.

A medical expert system asks about symptoms, applies rules from a knowledge base, and produces a diagnosis recommendation with the reasoning path it followed.

An expert system is not a human expert and is not automatically correct because experts supplied its rules. Its coverage is limited by the encoded knowledge and inference design.

Expert system: specialist rules plus an inference engine.

* [[artificial-intelligence|Artificial Intelligence (AI)]] * [[algorithm|Algorithm]] * [[system|System]] * [[machine-learning|Machine Learning]]

* [NIST, “An Overview of Artificial Intelligence and Robotics: Volume 1”](https://nvlpubs.nist.gov/nistpubs/Legacy/IR/nbsir83-2799.pdf) — defines expert systems as knowledge-and-reasoning programs for problems that ordinarily require human expertise.

* Compare [[artificial-intelligence|Artificial Intelligence (AI)]], [[algorithm|Algorithm]], [[system|System]], and [[machine-learning|Machine Learning]] to place Expert System in the surrounding system. * Follow the cited source material above for the method, standard, or research context behind this draft.