Evolving intelligent text-based agents
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Collaborative Kodama Agents with Automated Learning and Adapting for Personalized Web Searching
Proceedings of the Thirteenth Conference on Innovative Applications of Artificial Intelligence Conference
Dynamic self organizing maps for discovery and sharing of knowledge in multi agent systems
Web Intelligence and Agent Systems
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Web retrieval is now one of the most important issues in computer science, and we believe that applying multi-agent systems to this area is a promising approach. It is a straightforward idea to incorporate the idea of user modeling with machine learning methods into Web search services. Kodama, which is being developed and in use at Kyushu University, is a multi-agent-based Information Retrieval (IR) system that lets users retrieve more relevant distributed information from the Web. We report methods to agentify the Web, and to exploit User Preferences (UP) by the User Interface Agent (UIA), Interpretation Policy (IP) by the Web Page Agent (WPA) and the known Server Agents (SA) table by the SA adaptively.