Abstract
The rule-based approach to building intelligent systems is prevalent throughout the enterprise of Artificial Intelligence. Many famous systems have succeeded because they rely on rules at least to some extent. Through good knowledge engineering, the representation and encodement of the elements required to find adequate problem solutions can be facilitated. But despite enormous efforts, rule-based systems are far from perfect in their performance. What are the limitations and how can they be overcome?
The sponsors of the Center are McDonnell Douglas Corporation and Southwestern Bell Telephone Company.
The second author gratefully acknowledge the support of King Fahd University of Petroleum and Minerals.
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.
References
Mitchell P. Marcus, A Theory of Syntactic Recognition for Natural Language, MIT Press, Cambridge, MA, 1980.
Randall Davis, “Amplifying Expertise with Expert Systems,” in The AI Business: Commercial Uses of Artificial Intelligence, ed. P.H. Winston and K.A. Prendergast, MIT Press, Cambridge, MA, 1984.
Randall Davis, “Teiresias: Applications of Meta-Level Knowledge,” in Knowledge-Based Systems in Artificial Intelligence, ed. R. Davis and D.B. Lenat, McGraw-Hill, New York, NY, 1982.
M.F. St. John and J.L. McClelland, “Learning and Applying Contextual Constraints in Sentence Comprehension,” Technical Report AIP-39, Department of Psychology, Carnegie-Mellon University, Pittsburgh, PA, June 8, 1988.
E. Collins, S. Ghosh, and C.L. Scofield, “An Application of a Multiple Neural Network Learning System to Emulation of Mortgage Underwriting Judgements,” in Proceedings of IEEE International Confernce on Neural Networks II, pp. 459–466, 1988.
Kanaan A. Faisal and Stan C. Kwasny, “Deductive and Inductive Learning in a Connectionist Deterministic Parser,” in Proceedings of the International Joint Conference on Neural Networks, vol. 2, pp. 471–474, Lawrence Erlbaum Associates, Hillsdale, NJ, January 15–19, 1990.
Kanaan A. Faisal and Stan C. Kwasny, “Design of a Hybrid Deterministic Parser,” in Proceedings of the 13th International Conference on Computational Linguistics, Helsinki, Finland, August, 1990. ( FORTHCOMING )
Stan C. Kwasny and Kanaan A. Faisal, Connectionism and Determinism in a Syntactic Parser, Connection Science: Journal of Neural Comuting, Artificial Intelligence, and Cognitive Research — Special Issue on Connectionist Research on Natural Language, Carfax Publishing Company, Abingdon, Oxfordshire, England, 1990. (in press)
Eugene Charniak, “A Parser with Something for Everyone,” in Parsing Natural Language, ed. M. King, pp. 117–150, Academic Press, New York, NY, 1983.
Robert Milne, “Resolving Lexical Ambiguity in a Deterministic Parser,” Computational Linguistics, vol. 12, no. 1, pp. 1–12, January-March, 1986.
Robert C. Berwick, The Acquisition of Syntactic Knowledge, MIT Press, Cambridge, MA, 1985.
David E. Rumelhart, Geoffrey Hinton, and Ronald J. Williams, “Learning Internal Representations by Error Propagation,” in Parallel Distributed Processing, ed. D.E. Rumelhart and J.L. McClelland, pp. 318–364, MIT Press, Cambridge, MA, 1986.
Patrick H. Winston, Artificial Intelligence, Addison-Wesley, Reading, Ma, 1984.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1990 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kwasny, S.C., Faisal, K.A. (1990). Overcoming Limitations of Rule-Based Systems: An Example of a Hybrid Deterministic Parser. In: Dorffner, G. (eds) Konnektionismus in Artificial Intelligence und Kognitionsforschung. Informatik-Fachberichte, vol 252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76070-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-76070-9_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53131-9
Online ISBN: 978-3-642-76070-9
eBook Packages: Springer Book Archive