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Knowledge Representation: Features of Knowledge

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Fundamentals of Artificial Intelligence

Part of the book series: Springer Study Edition ((SSE))

Abstract

It is by now a cliché to claim that knowledge representation is a fundamental research issue in Artificial Intelligence (AI) underlying much of the research, and the progress, of the last fifteen years. And yet. it is difficult to pinpoint exactly what knowledge representation is, does, or promises to do. A thorough survey of the field by Ron Brachman and Brian Smith [Brachman & Smith 80] points out quite clearly the tremendous range in viewpoints and methodologies of researchers in knowledge representation. This paper is a further attempt to look at the field in order to examine the state of the art and provide some insights into the nature of the research methods and results. The distinctive mark of this overview is its viewpoint: that propositions encoded in knowledge bases have a number of important features, and these features serve, or ought to serve, as a basis for guiding current interest and activity in AI. Accordingly, the paper provides an account of some of the issues that arise in studying knowledge, belief, and conjecture, and discusses some of the approaches that have been adopted in formalizing and using some of these features in AI. The account is intended primarily for the computer scientist with little exposure to AI and Knowledge Representation, and who is interested in understanding some of the issues. As such, the paper concentrates on raising issues and sketching possible approaches to solutions. More technical details can be found in the work referenced throughout the paper.

Reprinted from Fundamentals in Man-Machine Communication: Speech, Vision and Natural Language, Jean-Paul Haton (Ed.), 1986, with permission from Cambridge University Press.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Toronto, Canada

    James P. Delgrande & John Mylopoulos (Senior fellow)

  2. Department of Computing Science, Simon Fraser University, Burnaby, BC, Canada

    James P. Delgrande

  3. Canadian Institute for Advanced Research, Canada

    John Mylopoulos (Senior fellow)

Authors
  1. James P. Delgrande
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  2. John Mylopoulos
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Editors and Affiliations

  1. Institut für Informatik, Technische Universität München, Postfach 202420, D-8000, München 2, Germany

    W. Bibel

  2. LIFIA-IMAG, BP 68, F-38402, St. Martin d’Hères Cédex, France

    Ph. Jorrand

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© 1987 Springer-Verlag Berlin Heidelberg

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Delgrande, J.P., Mylopoulos, J. (1987). Knowledge Representation: Features of Knowledge. In: Bibel, W., Jorrand, P. (eds) Fundamentals of Artificial Intelligence. Springer Study Edition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-40145-3_1

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  • DOI: https://doi.org/10.1007/978-3-662-40145-3_1

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