The primary application domain of Kodama is the WWW and its purpose in this application is to assist users to find desired information. Three different categories of Kodama’s agents are introduced here, Web Page Agents, Server Agents, and User Interface Agents. Kodama agents learn and adapt to the User’s Preferences (UP), which may change over time. At the same time, they explore these preferences to get any relevancy with the future queries. These communities of Kodama agents autonomously achieve and update their Interpretation Policies (IP) & UP and cooperate with other agents to retrieve distributed relevant information on the Web. This paper studies ways to model user’s interests and shown how these models can be deployed for more effective information retrieval. In terms of adaptation speed, the proposed methods make Kodama system acts as a pinpoint information retrieval system, converges to the user’s interests and adapts to the user’s sudden change of interests.