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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