Uncertainty-Sensitive Heterogeneous Information Fusion: Assessing Threat with Soft, Uncertain, and Conflicting Evidence

This report presents research on various methods for heterogeneous information fusion-combining data that are qualitative, subjective, fuzzy, ambiguous, contradictory, and even deceptive, in order to form a realistic uncertainty-sensitive assessment of threat. The context is counterterrorism, for both military and civilian applications, but the ideas are more generally applicable in intelligence and law enforcement.