Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems Laboratory

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Citation: Edward A. Feigenbaum and Robert S. Engelmore and Thomas R. Gruber and Yumi Iwasaki. (1990) Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems Laboratory. In KSL-90-83, November,1990.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Edward A. Feigenbaum and Robert S. Engelmore and Thomas R. Gruber and Yumi Iwasaki
title Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems Laboratory
number KSL-90-83
institution Knowledge Systems, AI Laboratory
address Stanford, CA, USA
year 1990
month November
Bibtex more
Access Paper
abstract We view the limitation of highly specialized, narrowly scoped knowledge bases as the single greatest impediment to achieving higher levels of competence inexpert systems and other AI programs. Programs must know more than they know today, and be able to use more general forms of knowledge, if they are to become more intelligent. To build programs with more generally useful knowledge will require advances in the representation of knowledge and appropriate reasoning processes.Our long-term goal is to explore the limits of performance/competence achievable by intelligent systems. Considering the principle that intelligent performance is strongly dependent on the knowledge given to systems, we are concentrating on the question of how to represent general-purpose scientific and engineering knowledge that can be used in a variety of important tasks.This paper summarizes the technical issues that motivate the How Things Work project, discusses some of the tangible results expected, and concludes with a section on the scientific and social importance of the research.

KSL Technical Report ID: KSL-90-83
Facts about Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems LaboratoryRDF feed
Abstract We view the limitation of highly specializ … We view the limitation of highly specialized, narrowly scoped knowledge bases as the single greatest impediment to achieving higher levels of competence inexpert systems and other AI programs. Programs must know more than they know today, and be able to use more general forms of knowledge, if they are to become more intelligent. To build programs with more generally useful knowledge will require advances in the representation of knowledge and appropriate reasoning processes.Our long-term goal is to explore the limits of performance/competence achievable by intelligent systems. Considering the principle that intelligent performance is strongly dependent on the knowledge given to systems, we are concentrating on the question of how to represent general-purpose scientific and engineering knowledge that can be used in a variety of important tasks.This paper summarizes the technical issues that motivate the How Things Work project, discusses some of the tangible results expected, and concludes with a section on the scientific and social importance of the research. fic and social importance of the research.
Address Stanford, CA, USA  +
Author Edward A. Feigenbaum and Robert S. Engelmore and Thomas R. Gruber and Yumi Iwasaki  +
Bibtype techreport  +
Has author Edward A. Feigenbaum and Robert S. Engelmore and Thomas R. Gruber and Yumi Iwasaki  +
Has identifier KSL-90-83  +
Has publishing details November,1990  +
Has title Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems Laboratory  +
Has where published KSL-90-83  +
Has year 1990  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-90-83  +
Month November  +
Number KSL-90-83  +
Process note NO  +
Title Large Knowledge Bases for Engineering: The How Things Work Project of the Knowledge Systems Laboratory  +
Year 1990  +
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