DIFFERENCE BETWEEN EXPERT SYSTEM
AND CONVENTIONAL SYSTEM
The principle distinction between expert systems and traditional problem
solving programs is the way in which the problem related expertise is coded. In
conventional applications, problem expertise is encoded in both program and
data structures. In the expert system approach all of the problem related
expertise is encoded in data structures only, none is in programs. Generally in
expert systems, the use of knowledge is vital. But in conventional system data
is used more efficiently than knowledge. Conventional systems are not capable
of explaining a particular conclusion for a problem. These systems try to solve
in a straight forward manner. But expert systems are capable of explaining how
a particular conclusion is reached and why requested information is needed
during a process. However, the problems are solved more efficiently than a
conventional system by an expert system. Generally in an expert system, it uses
the symbolic representations for knowledge i.e. the rules, different forms of
networks, frames, scripts etc. and performs their inference through symbolic
computations. But conventional systems are unable to express these terms. They
just simplify the problems in a straight forward manner and are incapable to
express the “how, why” questions. Also the problem solving tools those are
present in expert system are purely absent in conventional systems. The various
types of problems are always solved by the experts in an expert system. So the
solution of the problem is more accurate than a conventional system.
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