Learning for human-agent collaboration on the semantic Web

Semantic Web is a challenging framework to make Web information machine readable or understandable, but it seems not enough to make human´s requirements for collecting and utilizing information automatically. The Agent technology becomes hopeful approach to bridge the gap between humans and machines. Agents may be autonomous and intelligent entities that may travel among agents and human. They get the requirements from human or other agents, and offer an appropriate solution through consulting among them. The main difference between agent and ordinary software development is the issue of coordination, cooperation and learning. This issue is very important for utilizing the Web information. We attempt to give an overview and research challenges with respect to the combination of machine learning and agent technologies with semantic Web from the perspective of interaction as well as interoperability among agents and humans.