| R1-soar: an experiment in knowledge-intensive programming in a problem-solving architecture. | |
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MedLine Citation:
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PMID: 21869293 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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This paper presents an experiment in knowledge-intensive programming within a general problem-solving production-system architecture called Soar. In Soar, knowledge is encoded within a set of problem spaces, which yields a system capable of reasoning from first principles. Expertise consists of additional rules that guide complex problem-space searches and substitute for expensive problem-space operators. The resulting system uses both knowledge and search when relevant. Expertise knowledge is acquired either by having it programmed, or by a chunking mechanism that automatically learns new rules reflecting the results implicit in the knowledge of the problem spaces. The approach is demonstrated on the computer-system configuration task, the task performed by the expert system R1. |
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Authors:
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P S Rosenbloom; J E Laird; J McDermott; A Newell; E Orciuch |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: 7 ISSN: 0162-8828 ISO Abbreviation: IEEE Trans Pattern Anal Mach Intell Publication Date: 1985 May |
Date Detail:
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Created Date: 2011-08-26 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: United States |
Other Details:
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Languages: eng Pagination: 561-9 Citation Subset: - |
Affiliation:
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Departments of Computer Science and Psychology, Stanford University, Stanford, CA 94305. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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