Collaborative decision making and intelligent reasoning in judge advisor systems

This paper applies judgment and decision making research to collaborative problem solving. This analysis is done with respect to the Raven and CoRaven decision-making tools for filtering, interpreting, and visualizing large amounts of uncertain data in the domain of intelligence analysis. Raven and CoRaven are multimodal advisory decision aids and their inferential reasoning is based on Bayesian networks. Human decision makers and information sources interact with these decision making systems in many ways during their design, construction, refinement and usage. This paper analyzes the collaborative aspects of the use of Raven and CoRaven using the judge advisor system model.