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Building a knowledge base

  • Mark H. Lee
Part of the Open University Press Robotics Series book series (OUPRS)

Abstract

In the previous chapters we looked at the difficulties associated with sensory processing and now we turn our attention to the design and construction of knowledge bases which form the heart of intelligent systems. Such knowledge bases contain information derived from many sources, including sensors, and are used to support reasoning and planning processes. A knowledge base is a store of information but should not be confused with a database. Knowledge bases record data but are also able to manipulate, refine, modify and create data. Consequently, they are not just passive stores of facts but involve processing and self-modification.

Keywords

Knowledge Base Knowledge Representation Inference Rule Production Rule Theorem Prover 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Further reading material

  1. Basic material on the representation methods described here can be found in many AI textbooks; the general references cited in Chapter 1 are recommended.Google Scholar
  2. Avaluable collection of classic papers is Readings in Knowledge Representation, edited by R. J. Brachman and H. J. Levesque (Morgan Kaufmann, 1985).Google Scholar
  3. A special issue of the journal IEEE Computer (October 1983), volume 16 number 10, was revised and reprinted as a book: The Knowledge Frontier: Essays in the Representation of Knowledge, edited by Nick Cercone and Gordon McCalla (Springer-Verlag, 1987).Google Scholar
  4. Areview of the nature of knowledge and the important features that concern AI is: `Knowledge Representation: Features of Knowledge’, by James Delgrande and John Mylopoulos in Lecture Notes in Computer Science, number 232, edited by W. Bibel and Ph. Jorrand (Springer-Verlag, 1986 ).Google Scholar
  5. In an attempt to improve representation schemes to handle considerations like necessity, possibility, belief, time, and relative knowledge, AI workers have explored the potential of some of the more exotic non-standard systems of logic. Logics for Artificial Intelligence by R. Turner (Ellis Horwood Ltd., 1984), is a good review text giving details of modal logics, temporal logics and fuzzy logic.Google Scholar
  6. The original frames idea is described in a readable article by Marvin Minsky entitled `A Framework for Representing Knowledge’, in The Psychology of Computer Vision, edited by P. H. Winston (McGraw-Hill, 1975).Google Scholar
  7. Acollection of papers on production system topics is Pattern-Directed Inference Systems, edited by D. A. Waterman and F. Hayes-Roth (Academic Press, 1978).Google Scholar
  8. Readers interested in AI programming languages should consult Ivan Bratko’s excellent book Prolog Programming for Artificial Intelligence (Addison-Wesley, 1986). A good starting point for LISP programmers is Common Lisperaft by R. Wilensky (W.W. Norton, 1986).Google Scholar

Copyright information

© Mark H. Lee 1989

Authors and Affiliations

  • Mark H. Lee

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