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Expert System, a type of computer application program that makes decisions or solves problems in a particular field, such as finance or medicine, by using knowledge and analytical rules defined by experts in the field.
Human experts solve problems by using a combination of factual knowledge and reasoning ability. In an expert system, these two essentials are contained in two separate but related components, a knowledge base and an inference engine. The knowledge base provides specific facts and rules about the subject, and the inference engine provides the reasoning ability that enables the expert system to form conclusions. Expert systems also provide additional tools in the form of user interfaces and explanation facilities. User interfaces, as with any application, enable people to form queries, provide information, and otherwise interact with the system. Explanation facilities, an intriguing part of expert systems, enable the systems to explain or justify their conclusions, and they also enable developers to check on the operation of the systems themselves. Expert systems originated in the 1960s; fields in which they are used include chemistry, geology, medicine, banking and investments, and insurance.
Artificial Intelligence (AI), a term that in its broadest sense would indicate the ability of an artifact to perform the same kinds of functions that characterize human thought. The possibility of developing some such artifact has intrigued human beings since ancient times. With the growth of modern science, the search for AI has taken two major directions: psychological and physiological research into the nature of human thought, and the technological development of increasingly sophisticated computing systems.
In the latter sense, the term AI has been applied to computer systems and programs capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. The most important fields of research in this area are information processing, pattern recognition, game-playing computers, and applied fields such as medical diagnosis. Current research in information processing deals with programs that enable a computer to understand written or spoken information and to produce summaries, answer specific questions, or redistribute information to users interested in specific areas of this information. Essential to such programs is the ability of the system to generate grammatically correct sentences and to establish linkages between words, ideas, and associations with other ideas. Research has shown that whereas the logic of language structure—its syntax—submits to programming, the problem of meaning, or semantics, lies far deeper, in the direction of true AI.
In medicine, programs have been developed that analyse the disease symptoms, medical history, and laboratory test results of a patient, and then suggest a diagnosis to the physician. The diagnostic program is an example of so-called expert systems—programs designed to perform tasks in specialised areas as a human would. Expert systems take computers a step beyond straightforward programming, being based on a technique called rule-based inference, in which preestablished rule systems are used to process the data. Despite their sophistication, systems still do not approach the complexity of true intelligent thought.
Many scientists remain doubtful that true AI can ever be developed. The operation of the human mind is still little understood, and computer design may remain essentially incapable of analogously duplicating those unknown, complex processes. Various routes are being used in the effort to reach the goal of true AI. One approach is to apply the concept of parallel processing—interlinked and concurrent computer operations. Another is to create networks of experimental computer chips, called silicon neurons, that mimic data-processing functions of brain cells. Using analog technology, the transistors in these chips emulate nerve-cell membranes in order to operate at the speed of neurons.