TIBOR: A Resource-bounded Information Foraging Agent for Visual Analytics

Visual analytics is the science of applying reasoning and analysis techniques to large, complex real-world data for problem solving using visualizations. Real world knowledge gathering and investigative tasks are very complex because the problem-solving context is constantly evolving, and the data may be incomplete, unreliable and/or conflicting. We describe a mixed-initiative reasoning agent that will assist investigative analysts to choose from and reason about enormous databases of text, imagery, video and Webcast. This agent leverages sequential decision making and an AI blackboard system to support hypothesis tracking and validation in a highly uncertain environment. Resource-bounded control mechanisms enable the agent to reason about the uncertainty. We have also designed a user interface that will enable analysts to gather and sift large amounts of evidence and to collaborate with and, where necessary, to control the agent.