Knowledge Acquisition, Knowledge Programming, and Knowledge Refinement.

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Title: Knowledge Acquisition, Knowledge Programming, and Knowledge Refinement.
Language: English
Authors: Hayes-Roth, Frederick, Rand Corp., Santa Monica, CA.
Availability: Rand Corporation, Main St., Santa Monica, CA 90406 ($3.00).
Peer Reviewed: N
Page Count: 39
Publication Date: 1980
Sponsoring Agency: National Science Foundation, Washington, DC.
Contract Number: MCS77-03273
Report Number: Rand-R-2540-NSF
Document Type: Reports - Research
Descriptors: Artificial Intelligence, Computers, Information Theory, Man Machine Systems, Programing, Research Reports, Systems Development
Geographic Terms: U.S.; California
ISBN: 978-0-8330-0195-5
Abstract: This report describes the principal findings and recommendations of a 2-year Rand research project on machine-aided knowledge acquisition and discusses the transfer of expertise from humans to machines, as well as the functions of planning, debugging, knowledge refinement, and autonomous machine learning. The relative advantages of humans and machines in the building of intelligent systems are explained. Background and guidance is provided for policymakers concerned with the research and development of machine-based learning systems. The research method adopted emphasized iterative refinement of knowledge in response to actual experience; i.e., a machine's knowledge was acquired initially from a human who provided enough concepts, constraints, and problem-solving heuristics to define some minimal level of performance. Sixty-two references are listed. (Author/FM)
Journal Code: RIESEP1981
Entry Date: 1981
Accession Number: ED201337
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED201337
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PubType: Report
PubTypeId: report
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  Label: Title
  Group: Ti
  Data: Knowledge Acquisition, Knowledge Programming, and Knowledge Refinement.
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  Data: English
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Hayes-Roth%2C+Frederick%22">Hayes-Roth, Frederick</searchLink><br /><searchLink fieldCode="AR" term="%22Rand+Corp%2E%2C+Santa+Monica%2C+CA%2E%22">Rand Corp., Santa Monica, CA.</searchLink>
– Name: Avail
  Label: Availability
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  Data: Rand Corporation, Main St., Santa Monica, CA 90406 ($3.00).
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: N
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 39
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 1980
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Science Foundation, Washington, DC.
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  Label: Contract Number
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  Data: MCS77-03273
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  Label: Report Number
  Group: ID
  Data: Rand-R-2540-NSF
– Name: TypeDocument
  Label: Document Type
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  Data: Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computers%22">Computers</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Theory%22">Information Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Man+Machine+Systems%22">Man Machine Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Programing%22">Programing</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Reports%22">Research Reports</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+Development%22">Systems Development</searchLink>
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  Data: 978-0-8330-0195-5
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This report describes the principal findings and recommendations of a 2-year Rand research project on machine-aided knowledge acquisition and discusses the transfer of expertise from humans to machines, as well as the functions of planning, debugging, knowledge refinement, and autonomous machine learning. The relative advantages of humans and machines in the building of intelligent systems are explained. Background and guidance is provided for policymakers concerned with the research and development of machine-based learning systems. The research method adopted emphasized iterative refinement of knowledge in response to actual experience; i.e., a machine's knowledge was acquired initially from a human who provided enough concepts, constraints, and problem-solving heuristics to define some minimal level of performance. Sixty-two references are listed. (Author/FM)
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  Label: Entry Date
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  Data: 1981
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 39
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Computers
        Type: general
      – SubjectFull: Information Theory
        Type: general
      – SubjectFull: Man Machine Systems
        Type: general
      – SubjectFull: Programing
        Type: general
      – SubjectFull: Research Reports
        Type: general
      – SubjectFull: Systems Development
        Type: general
      – SubjectFull: U.S.; California
        Type: general
    Titles:
      – TitleFull: Knowledge Acquisition, Knowledge Programming, and Knowledge Refinement.
        Type: main
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            NameFull: Rand Corp., Santa Monica, CA.
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            NameFull: Hayes-Roth, Frederick
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              M: 05
              Type: published
              Y: 1980
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            – Type: isbn-print
              Value: 978-0-8330-0195-5
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