Abstract
Knowledge Based Systems (KBS) are computer programs in which knowledge and control arc explicitly separated. In first generation KBS, the reasoning is usually monotonic and the control is procedural. Second generation KBS usually exhibit nonmonotonic reasoning, declarative control, and more sophisticated representations of uncertainty. We will focus on the first generation KBS and analyze their typical architecture, composed of a Knowledge Base (KB), a Working Memory (WM), and an Inference Engine (IE). The KB describes the domain knowledge; the WM describes a problem instance; the IE determines the applicability of different subsets of the KB to the current problem. The selection of a specific knowledge representation paradigm, used to build the KB, implicitly determines the selection of the inference mechanism to be used. We will briefly discuss Predicate Calculus, which uses unification and resolution, Frames, which use inheritance, and Production Rules, which use rule chaining.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
William J. Clanccy. Classification Problem Solving. In Proceedings Fourth National Conference on Artificial Intelligence, pages 49–55. AAAI, August 1984.
E.H. Shortliffe and B. Buchanan. A Model of Inexact Reasoning in Medicine. Mathematical Biosciences, 23:351–379, 1975.
B.G. Buchanan and E.H. Shortliffe. Rule-Based Expert Systems. Addison-Wesley, Reading, Massachusetts, 1984.
Wendy B. Rauch-Hindin. Artificial Intelligence in Business, Science, and Industry. Prentice Hall, 1985.
R.O. Duda, J. Gaschnig, P.E. Hart, K. Konolige, Reboh R., P. Barrett, and J. Slocum. Development of a computer-based consultant for mineral exploration. Sri project 5821 final report and sri project 6415 annual report, SRI International, Artificial Intelligence Center, Menlo Park, California, 1978.
P. P. Bonissone. Delta: An expert system to troubleshoot diesel electric locomotives. In Proceeding of ACM 83, pages 44–45. ACM, New York, 1983.
P. P. Bonissone and H. E. Johnson. Expert system for diesel electric locomotive repair. Human Systems Management, 4:255–262, 1984.
Piero P. Bonissone and Nancy C Wood. Plausible Reasoning in Dynamic Classification Problems. In Proceedings of the Validation and Testing of Knowledge-Based Systems Workshop. AAAI, August 1988.
Intellicorp. KEE Software Development System User’s Manual, 1986. Version 3.0.
Inference. ART Reference Manual, 1987. Version 3.0.
Piero P. Bonissone, Stephen Gans, and Keith S. Decker. RUM: A Layered Architecture for Reasoning with Uncertainty. In Proceedings 10th International Joint Conference on Artificial Intelligence, pages 891–898. AAAI, August 1987.
W.B. Gevarter. Expert Systems: limited but powerful. IEEE Spectrum, 20(8):39–45, 1983.
N.J. Nilsson. Problem-Solving Methods in Artificial Intelligence. McGraw-Hill, 1971.
Chin-Liang Chang and Richard Char-Tung Lee. Symbolic Logic and Mechnaical Theorem Proving. Acadermic Press, 1973.
W.J. Rapaport. Predicate Logic. In Stuart Shapiro, Editor, Encyclopedia of Artificial Intelligence, pages 538–544. John Wiley and Sons Co., New York, 1987.
M. Minsky. A Framework for Representing Knowledge. In P. Winston, Editor, The Psychology of Computer Vision, pages 211–277. McGraw-Hill, New York, 1975.
R.Schank and R.P. Abelson. Scripts, Plans, Goals, and Understanding. Erlbaum, Hillsdale, N.J., 1977.
F.C. Bartlett. Remembering: A Study in Experimental And Social Psychology. The University Press, Cambridge, 1932. Revised 1961.
J. Moore and A. Newell. How can Merlin Understand? In L.W. Gregg, Editor, Knowledge and Cognition, pages 201–252. Erlbaum, 1973.
M.R. Quillian. Semantic Memory. In M. Minsky, Editor, Semantic Information Processing. M.I.T. Press, Cambridge, MA., 1968.
A.S. Maida. Frame Theory. In Stuart Shapiro, Editor, Encyclopedia of Artificial Intelligence, pages 302–312. John Wiley and Sons Co., New York, 1987.
A.A. Markov. The Theory of Algorithms (Russian). Trudy Mathematicheskogo Instituta imeni V.A. Steklova, 38:176–189, 1951. Translated from the Russian by J.J. Schorr-Kon, U.S. Department of Commerce, Office of Technical Services, number OTS 60-51085.
H.R. Lewis and C. H. Papadimitriou. Elements of the Theory of Computation. Prentice Hall, 1981.
C. Forgy and J. McDermott. OPS, a domain-independent production system language. In Proc. Fifth Intern. Conf. on Artificial Intelligence, pages 933–939, 1977.
Lee Brownston, Robert, Elaine Kant, and Nancy Martin. Programming Expert Systems in OPS5. Addison-Wesley, Reading, Massachusetts, first edition, 1985.
F. Hayes-Roth, D. Waterman, and D.Lenat (Eds.). Builiding Expert Systems. Addison-Wesley, 1983.
J. McDermott and C. Forgy. Production System Conflict Resolution Strategies. In D. Waterman and F. Hayes-Roth, Editors, Pattern-Directed Inference Systems, pages 177–199. Academic Press, New York, 1978.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1989 Springer-Verlag Berlin, Heidelberg
About this paper
Cite this paper
Bonissone, P.P. (1989). Knowledge Representation and Inference in Knowledge Based Systems (Expert Systems). In: Jovanović, A.S., Kussmaul, K.F., Lucia, A.C., Bonissone, P.P. (eds) Expert Systems in Structural Safety Assessment. Lecture Notes in Engineering, vol 53. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83991-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-83991-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-51823-5
Online ISBN: 978-3-642-83991-7
eBook Packages: Springer Book Archive