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.