Content analysis for proactive intelligence: marshaling frame evidence
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Bayesian networks for social modeling
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Calibrating bayesian network representations of social-behavioral models
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Technosocial predictive analytics in support of naturalistic decision making
NDM'09 Proceedings of the 9th Bi-annual international conference on Naturalistic Decision Making
Hi-index | 0.00 |
Illicit nuclear trafficking networks are a national security threat. These networks can directly lead to nuclear proliferation, as state or nonstate actors attempt to identify and acquire nuclear weapons-related expertise, technologies, components, and materials. The ability to characterize and anticipate the key nodes, transit routes, and exchange mechanisms associated with these networks is essential to influence, disrupt, interdict or destroy the function of the networks and their processes. The complexities inherent to the characterization and anticipation of illicit nuclear trafficking networks requires that a variety of modeling and knowledge technologies be jointly harnessed to construct an effective analytical and decision making workflow in which specific case studies can be built in reasonable time and with realistic effort. In this paper, we explore a solution to this challenge that integrates evidentiary and dynamic modeling with knowledge management and analytical gaming, and demonstrate its application to a geopolitical region at risk.