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2020 | OriginalPaper | Chapter

4. Systems Become Experts

Author : Klaus Mainzer

Published in: Artificial intelligence - When do machines take over?

Publisher: Springer Berlin Heidelberg

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Abstract

Knowledge-based expert systems are computer programs that store and accumulate knowledge about a specific area, from which knowledge automatically draws conclusions in order to offer solutions to concrete problems in that area. In contrast to the human expert, however, the knowledge of an expert system is limited to a specialized information base without general and structural knowledge about the world.
In order to build an expert system, the knowledge of the expert must be laid down in rules, translated into a program language and processed with a problem-solving strategy. The architecture of an expert system therefore consists of the following components: Knowledge base, problem-solving component (derivation system), explanatory component, knowledge acquisition, dialogue component. The coordination of these components is shown in Fig. 4.1.
Knowledge is the key factor in the representation of an expert system. There are two types of knowledge. One kind of knowledge concerns the facts of the field of application, which are recorded in textbooks and journals. Equally important is the practice in the respective area of application as knowledge of the second kind. It is heuristic knowledge on which judgement and any successful problem-solving practice in the field of application are based. It is knowledge of experience, the art of successful presumption, which a human expert acquires only in many years of professional work.

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Metadata
Title
Systems Become Experts
Author
Klaus Mainzer
Copyright Year
2020
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-59717-0_4

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