Execution Learning Domain Model Output

With the vast number of information resources available today, a critical problem is how to locate , retrieve and process information. It would be impractical to build a single uniied system that combines all of these information resources. A more promising approach is to build specialized information retrieval agents that provide access to a subset of the information resources and can send requests to other information retrieval agents when appropriate. In this paper we present the architecture of the individual information retrieval agents and describe how this architecture supports a network of cooperating information agents. We describe how these information agents represent their knowledge, communicate with other agents, dynamically construct information retrieval plans, and learn about other agents to improve eeciency. We have already built a small network of agents that have these capabilities and provide access to information for transportation planning.