Contextual Sociocultural Reasoning in Weak Signal Environments

Successful military actions are increasingly dependent on their compatibility with the sociocultural and environmental landscape in which they occur. Pre-emptive actions require the identification of populations that are becoming vulnerable to conflict, and locations that are breeding grounds for terrorism. The challenge is to identify the"signal within the noise"within the massive array of disparate data and to identify through data fusion the various indicators or combination of indicators that reveal the critical characteristics for decision-making. In Phase I we successfully provided a proof-of-concept for a deployable, automated decision-making tool that fuses diverse social, cultural, economic, political, and environmental data for predicting the success of proposed military actions in areas of interest and providing early warnings and alerts for activities that are precursors for hostile responses, outbreaks of conflict, and breeding grounds for terrorism. In Phase II we will be developing a fully operational proto-type that was demonstrated to be feasible under Phase I, and that can go to commercialization.