Modeling and Prediction of Asymmetric Threat Learning Processes

The USN is seeking innovative solutions to model and aid in the prediction of enemy course of action with emphasis on learning, adaptation, and intent. While analysts and strategists are well-versed in tracking threats against conventional military targets, the new asymmetric threats posed by insurgents and terrorist organizations alike, are much more difficult to anticipate. Given the events and challenges that the world faces in response to the continuing Global War on Terrorism (GWoT), this SBIR is particularly timely and important; and our company is in position to bring truly relevant work and experience to the solution. Namely, for the Phase I herein we propose to leverage ongoing work in this technology space (i.e., an ongoing program researching linear structural relations modeling in non-physical network analysis) by using that expertise to transcend solutions (both proposed or existing). We refer to this advancing and dynamic toolset as eX-urgent. We believe eX-urgent offers a radically different coarse of action (COA) prediction approach in that it will help capture, qualify and quantify the relationships of culture and subsequent human behavior to other important predictive variables that contribute to a subject’s decision-making process. By examining complex reciprocal causation, structural relations focuses on true combined cultural behavior and individual attributes. BENEFITS: While there are numerous works on criminal, terrorist, or enemy event prediction, we know of no eX-urgent –type solutions using the methods we offer; yet with the growing emphases on understanding those factors that influence actions by other mores, the civil and military user communities are actively searching for fundamental breakthroughs along these themes (especially when factoring in GWoT). Subsequently, we believe that this offers an ideal opportunity for commercialization of an eventual software solution(s) during Phase II and beyond. Furthermore, by teaming with our contacts in academia -- where the emphasis is to ensure that any solution adheres to grounded theoretical expectations -- a higher probability exists for combining our commercialization strength with the continuing innovations and additions to the eX-urgent toolset.