Alexander Pasik
Abstract
The structure and organization of expert systems can be usefully modeled after corresponding human experts. Often this modeling degrades because of insufficient expressive power in production system languages. Relational table techniques provide additional abstraction capabilities and are useful in extending the expressiveness of production system rules; the resulting systems can be easier to build, understand and debug because they can reflect more accurately human methods of reasoning. The number of superfluous rules is reduced by organizing much of the problem domain knowledge in relations in working memory. The relational table methods also provide a tool for the interfacing of knowledge bases and databases.
- Forgy, C. L. "OPSS User's Manual" Technical Report, Carnegie-Mellon University, Department of Computer Science, 1981.Google Scholar
- Lerner, M. and Cheng, J. "The Manhattan Mapper" Expert Systems Course Project, Columbia University, Department of Computer Science, 1983. (unpublished)Google Scholar
- McDermott, J. "R1: A Rule Based Configurer of Computer Systems" Artificial Intelligence, Volume 19(1), pp. 39--88, September 1982.Google ScholarDigital Library
- Newell, A. "Heuristic Programming: III-structured Problems" In J. S. Aronofsky (Ed.), Progress in Operations Research, John Wiley and Sons, pp. 361--414, 1969.Google Scholar
- Stolfo, S. J. and Vesonder, G. "ACE: An Expert System Supporting Analysis and Management Decision Making" Technical Report, Columbia University, Department of Computer Science, 1982.Google Scholar
- Walker, A. "Data Bases, Expert Systems, and Prolog" Technical Report RJ 3870, IBM Research Laboratory San Jose, 1983.Google Scholar
Index Terms
- Table-driven rules in expert systems
Recommendations
Domain-specific languages in Prolog for declarative expert knowledge in rules and ontologies
We use domain-specific languages and deductive databases for declarative rule bases.We present the design and implementation of DSLs for declarative expert rules in Prolog as an internal and as an external DSL.Our approach makes use of Prologs term-...
Expert-Driven Knowledge Discovery
ITNG '08: Proceedings of the Fifth International Conference on Information Technology: New GenerationsKnowledge Discovery techniques find new knowledge about a domain by analysing existing domain knowledge and examples of domain data. These techniques typically involve using a human expert and automated software analysis (Data Mining). Often the human ...
Maintainable process model driven online legal expert systems
AbstractLegal expert systems are computer applications that can mimic the consultation process of a legal expert to provide advice specific to a given scenario. The core of these systems is the experts’ knowledge captured in a sophisticated and often ...
Comments