Programs that use knowledge, facts, and reasoning techniques to solve problems that can only be solved by an expert. An expert system combines a knowledge base containing accumulated experience and a set of rules to be applied to the knowledge base in certain situations described to the program. The system will learn from experience just like humans.
Edward Feigenbaum explains that the world is moving from data processing to knowledge processing made possible by new processor technologies and computer architectures.
In 1960 expert systems were developed by the Artificial Intelligence Corporation which was dominated by the belief that reason when combined with sophisticated computer systems would produce expertise. The expert system that emerged at that time was GPS (General Purpose Problem-Solver) which changed the initial state into a predetermined goal. In the 1970s expert systems were derived from specialized knowledge rather than from formalism and use inference. And in 1980 the expert system began to be developed from academic to commercial.
The purpose of an expert system is actually to transfer knowledge from an expert to a computer which will then be passed on to other people who are not experts. Expert systems have played a large role in many industries including in financial services, telecommunications, healthcare, customer service, transportation, video games, manufacturing, aviation, and written communications. Two early expert systems solved the field of health care for medical diagnosis: Dendral, which helps chemists identify organic molecules, and MYCIN, which helps identify bacteria such as bacteremia and meningitis, and to recommend antibiotics and doses.
