Forward Slope Incorporated — Department of Defense SBIR Phase I: N211-079

Description

While Naval decisions happen at specific points in time, Naval decision-makers need to integrate the history of observed events to put those decisions in context. As multi-domain kill-chains analytics generate more events, this mental integration problem is becoming more challenging. There is a growing need for next generation Artificial Intelligence / Machine Learning (AI/ML) geospatial and non-geospatial data analytics to link events together into meaningful patterns and actionable visual representations. Under Jericho, the team will conduct a study to determine optimum algorithms to perform advanced analytics on geospatial and non-geospatial data, with an emphasis on temporal data alignment and explanatory representations. Abductive reasoning scale questions will be addressed by investigating architectural mechanisms for containerizing and distributing temporal period identification and abductive reasoning algorithms. The learning of abductive reasoning rules at scale will be investigated by evaluating Inductive Learning methods on Navy collected data sets. The result of Phase I will be a technical solution description, a demonstration of existing current temporal period identification and explanatory reasoning algorithms, an initial feasibility study, and a Phase II development plan.