Authors:
Grzegorz J. Nalepa
and
Igor Wojnicki
Affiliation:
Institute of Automatics, AGH – University of Science and Technology, Poland
Keyword(s):
Rule-based programming, software modelling, knowledge engineering, automated implementation, XTT.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Software Engineering
;
Symbolic Systems
Abstract:
Rule-based programming paradigm is omnipresent in number of engineering domains. However, there are some fundamental semantical differences between it, and classic procedural, or object-oriented approaches. Even though, there has been a lot of effort to use rules to model business logic in classic software no generic solution has been provided so far. In this paper a new approach for generalized rule-based programming is given. It is based on a use of advanced rule representation, which includes an extended attribute-based language, a non-monotonic inference strategy, with explicit inference control on the rule level. The paper shows how some typical programming constructions, as well as classic programs can be modelled in this approach. The approach can largely improve both the design and the implementation of complex software.