expert system

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Expert system

A software system designed to emulate the processes and procedures conducted by humans in particular areas of expertise, thereby automating decision-making processes.

expert system

a COMPUTER programme which simulates the problem-solving and decision-making behaviour of a technical expert in a particular field such as engineering and medicine. Like human technical experts, expert systems are able to learn from experience and restructure their knowledge in order to improve their future problem-solving.
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Acquiring knowledge is an important stage in creating expert systems: it is achieved by the knowledge engineer who needs to have a good knowledge of the methods of representing knowledge, methods provided by knowledge engineering such as: the method based on production rules; the method based on semantic nets; the frame-based method; the method based on logical models (propositional logic, the logic of predicates of the 2nd order); the method based on probabilistic logic (Bayesian logic); the method based on fuzzy set and logic (Moise, 2007).
5] In order to lessen the difficulty of performing knowledge acquisition and to better educate students on this subject, multimedia aids and automated knowledge acquisition tools are needed to support the knowledge engineer.
Expert systems are becoming more userfriendly and are requiring fewer computer skills by the knowledge engineer.
Knowledge Engineer An individual whose specialty is assessing problems, acquiring knowledge, and building knowledge systems.
At that time, they realized that they couldn't learn all there was to know on their own--they needed the help of a knowledge engineer and turned to IBM for help.
During the second state, conceptualization, the expert and knowledge engineer discuss and determine the key concepts, data relationships and information-flow characteristics that describe the problem-solving process.
The knowledge engineer interviews one or more experts and then distills the information relevant to the application into a set of rules or some other form of knowledge representation that reflects the behavior of human experts.
Because of hidden assumptions, the expert and knowledge engineer have blind spots.
The DISCIPLE approach attempts to change the way intelligent agents are built, from "being programmed" by a knowledge engineer to "being taught" by a user who does not have prior knowledge engineering or computer science experience.
The challenge then became to facilitate the knowledge-engineering process by designing a common language between the knowledge engineer and the domain expert.
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