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Machine learning research 1989-90Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.
Document ID
19910023512
Acquisition Source
Legacy CDMS
Document Type
Contractor Report (CR)
Authors
Porter, Bruce W. (Houston Univ. TX., United States)
Souther, Arthur (Texas Univ. Austin., United States)
Date Acquired
September 6, 2013
Publication Date
June 1, 1990
Subject Category
Computer Programming And Software
Report/Patent Number
NAS 1.26:188828
NASA-CR-188828
Accession Number
91N32826
Funding Number(s)
CONTRACT_GRANT: NCC9-16
PROJECT: RICIS PROJ. ET-14
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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