Extending Legacy Agent Knowledge Base Systems With Semantic Web Compatibilities

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.