Authors:
Po-Chun Chen
;
Guruprasad Airy
;
Prasenjit Mitra
and
John Yen
Affiliation:
The Pennsylvania State University, United States
Keyword(s):
Knowledge base, Rule-based system, Semantic web, Agent.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Databases and Information Systems Integration
;
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
;
Legacy Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Knowledge bases with inference capabilities play a significant role in an intelligent agent system. Towards the vision of the semantic Web, the compatibility of knowledge representation is critically important. However, a legacy system that was developed without this consideration would have compatibility gaps between its own knowledge representation and the semantic Web standards. In order to solve this problem, we present a systematical approach to extend a legacy agent knowledge base to be able to handle and reason information encoded in standard semantic Web languages. The algorithms presented in this paper are applicable to compatible rule-based systems, and the methodology can be applied to other knowledge systems.