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Expert Systems
In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by Automated reasoning system, reasoning through bodies of knowledge, represented mainly as Rule-based system, if–then rules rather than through conventional procedural programming code. Expert systems were among the first truly successful forms of AI software. They were created in the 1970s and then proliferated in the 1980s, being then widely regarded as the future of AI — before the advent of successful artificial neural networks. An expert system is divided into two subsystems: 1) a ''knowledge base'', which represents facts and rules; and 2) an ''inference engine'', which applies the rules to the known facts to deduce new facts, and can include explaining and debugging abilities. History Early development Soon after the dawn of modern computers in the late 1940s and early 1950s, researche ...
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CADUCEUS (expert System)
CADUCEUS was a medical expert system, an early type of recommender system - by Harry Pople of the University of Pittsburgh. Finished in the mid-1980s, it was built on the Internist-I, INTERNIST-1 algorithm (1972-1973). In its time, CADUCEUS was described as the "most knowledge-intensive expert system in existence".The Fifth Generation. Edward A. Feigenbaum and Pamela McCorduck. Addison-Wesley, Reading, Ma 01867, 275 Pp. Feb 1, 1984 CADUCEUS eventually could diagnose up to 1000 different diseases. The knowledge base was built on Pople's years of interviews with Jack Myers (biologist), Dr. Jack Meyers, one of the top internal medicine diagnosticians and a professor at the University of Pittsburgh. Their motivation was to improve on MYCIN, a recommender which focused on blood-borne infectious bacteria and instead embrace all internal medicine. While CADUCEUS worked using an inference engine similar to MYCIN's, it made a number of changes. As there can be a number of simultaneous dis ...
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