Concepts for an Agent-Based Visualization Tool for Presentation of Information with Uncertainty

To facilitate decision making tasks it is necessary to be able to "see" the situation. An enormous array of intelligence gathering, database, and sensor sources of information are available. Methods for visualizing the information must be established and information presented in such a way that human attention is captured and maintained on the most critical aspects of the information. Visualizations need to adapt to the changing circumstances to show the most relevant information at that time. We are developing a system called Holistic Analysis, Visualization, & Characterization Assessment Tool (HAVCAT) that uses intelligent agents that interact with the user to provide the correct information at the right time. This cutting edge system will enable visualization researchers to investigate techniques for adjusting visualizations based on user performance HAVCAT will employ domain ontologies to determine relationships within the data. The HAVCAT evidence reasoning agent distills the data and extracts the most pertinent actions or consequences. This paper describes the HAVCAT concepts and also research issues related to development of HAVCAT and techniques for directing user attention.