Document (#29258)

Author
Li, L.X.
Xu, L.D.
Title
Knowledge-based problem solving
Source
Encyclopedia of library and information science. Vol.71, [=Suppl.34]
Imprint
New York : Dekker
Year
2002
Pages
S.209-228
Abstract
Knowledge-based problem solving is a branch of artificial intelligence (AI) that has evolved in the last two decades and attempts to both capture knowledge and perform tasks that would normally require a human expert. It is a broad concept encompassing disciplines such as AI and technologies such as knowledge-based systems (KBSs). Artificial intelligence is commonly understood as a field of computer science that is concerned with the automation of human intelligent behavior (1). Westlake distinguishes three areas of AI: (1) work an solutions not thought about before, (2) problem solving that requires AI, and (3) knowledge-based problem solving (2). The last two are being applied in knowledge-based problem solving, but the first is still in the elementary stage. Also called expert systems, KBSs have been created as a result of AI research. They use domain-specific knowledge to provide high-quality solutions to the problems in a particular domain. They are made up of knowledge-based components that emulate the reasoning processes of a human expert and enable expert knowledge to be structured, coded, stored, and retrieved, and then to be extracted and used for application purposes. The relationship between knowledge-based problem solving and KBS is that knowledge-based problem-solving methods are a means of describing the reasoning process of KBS. A KBS is a problem-solving system whose architecture facilitates the usage of knowledge for problem solving in a particular problem domain. Knowledge-based systems have been applied to solve problems in the areas of medical diagnosis, mining, ecological systems management, transportation, public health, design, planning, and so on. More recently, commercial applications of KBS are widely available. A knowledge-based problem-solving approach alters the way business operates by changing the means that people traditionally use to solve business problems. For example, it provides more alternatives for business and industry to solve productivity problems and enables business and industry to reorganize and reengineer themselves to be more efficient and effective.

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