Intelligent Agents for E-Learning

Abstract

We propose the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in consultancy situations. Intelligent software agents act as clients and advisors using their knowledge in order to assist human users. In the proposed architecture the domain knowledge is semantically modeled by means of XML-based ontology languages such as OWL. Using an inference engine the agents reason on base of their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand private data, which has to be protected against unauthorized access, and on the other hand publicly accessible data spread over different web sites. Comparable to a real consultancy situation, an agent only reveals sensitive private data if it is indispensable for finding a solution. In addition, depending on the actual consultancy situation each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. The usefulness of our approach is proved by the implementation of an advisory system whose objective is to develop virtual student advisers that render support to university students in order to successfully organize und perform their studies.