Intelligent Information Gathering Using Decision Models

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To investigate coordinated information gathering. The vast amount of information available today on the National Information Infrastructure has a great potential to improve the quality of decisions and the productivity of consumers of this information. Rapid expansion of the amount of available information and the number of sources is expected over the next 5-10 years. Improved information retrieval and information extraction technologies will become available. The large number of information sources that are currently emerging and their different levels of accessibility, reliability, and associated costs present a complex information gathering coordination problem that a human decisionmaker cannot possibly solve without high-level filtering of information. To be able to exploit the great potential of the NII we propose to develop the next logical step in automation of information gathering tasks: to organize information gathering activity based on its marginal contribution to the quality of the user's decision or task. This approach emphasizes the fact that information gathering is an intermediate step of a decisionmaking process. This research will provide a system with an explicit representation of the user's decision model, so that information gathering activity can be organized on the basis of its effect on the quality of the decision. To automate the information gathering planning task, the research will investigate an innovative extension to the standard value-of-information theory, that addresses the problems of information reliability, retrieval costs, real-time operation, and uncertainty. When operating under resource constraints (related to the cost of communication and database access, limited computation power, and limited amount of time) this approach should achieve a significant performance improvement over current techniques