ABSTRACT
Expert systems differ in important ways from both conventional information systems and systems developed in other branches of artificial intelligence. Among the characteristics that make expert systems distinctive are symbolic representation, symbolic reasoning, natural language processing, heuristics search, and reasoning processing capabilities. Expert systems are valuable in applications that call for judgment and inference based on incomplete data. In the medical field, expert systems are used to screen patients, provide second opinions, and check the accuracy of a diagnosis. Geologists use expert systems to help locate oil and mineral deposits. Expert systems should be considered only when the need for judgment and/or the lack of complete data make traditional algorithm-based systems unacceptable. A user accesses the system through a user interface called the expert system shell and enters the parameters of a problem to an inference engine. An expert system evolves over time, calling for almost constant revision, a trait expert systems share with most prototypes.
