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Qualitative application languages for knowledge acquisition

Qualitative application languages for knowledge acquisition Artificial Intelligence Review (1990) 4, 157-162 Response Time Stuart H. Rubin Department of Computer Science, Central Michigan University knowledge is said to be acquired by default Many researchers have adopted the reasoning. Such reasoning underpins what perspective that problem solving, learning, and explanation can be conceptualized in we term commonsense knowledge. terms of model acquisition, representation, When purely quantitative reasoning is and use (Clancey, 1989). Schweickert et al. used, many complex problems cannot be solved (Bennett, 1987). The realization of (Artificial Intelligence Review, 1987, 1, pp. 245-253) report on a preliminary study this bottleneck has led many researchers to of three techniques used to elicit knowledge turn instead to qualitative models and hybrid models of commonsense reasoning bases. The techniques were the structured (Rubin, 1989). For example, Nordhausen & interview, 'twenty questions', i.e. imputing Langley (1987) report an integrated rules from information requests, and a card discovery system, IDS, which first finds sort. Their study supports the well-known qualitative laws in the domain of heat finding that knowledge acquisition is one of the major bottlenecks in expert system phenomena and then utilizes the resultant development. qualitative schemas to constrain a search for Knowledge is essential for intelligence. quantitative laws. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

Qualitative application languages for knowledge acquisition

Rubin, Stuart
Artificial Intelligence Review , Volume 4 (3) – Jun 9, 2004
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References (16)

Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; Computer Science, general
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/BF00140675
Publisher site
See Article on Publisher Site

Abstract

Artificial Intelligence Review (1990) 4, 157-162 Response Time Stuart H. Rubin Department of Computer Science, Central Michigan University knowledge is said to be acquired by default Many researchers have adopted the reasoning. Such reasoning underpins what perspective that problem solving, learning, and explanation can be conceptualized in we term commonsense knowledge. terms of model acquisition, representation, When purely quantitative reasoning is and use (Clancey, 1989). Schweickert et al. used, many complex problems cannot be solved (Bennett, 1987). The realization of (Artificial Intelligence Review, 1987, 1, pp. 245-253) report on a preliminary study this bottleneck has led many researchers to of three techniques used to elicit knowledge turn instead to qualitative models and hybrid models of commonsense reasoning bases. The techniques were the structured (Rubin, 1989). For example, Nordhausen & interview, 'twenty questions', i.e. imputing Langley (1987) report an integrated rules from information requests, and a card discovery system, IDS, which first finds sort. Their study supports the well-known qualitative laws in the domain of heat finding that knowledge acquisition is one of the major bottlenecks in expert system phenomena and then utilizes the resultant development. qualitative schemas to constrain a search for Knowledge is essential for intelligence. quantitative laws.

Journal

Artificial Intelligence Review – Springer Journals

Published: Jun 9, 2004

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