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Expert Systems / AI
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Expert System
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
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.
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