Traditional military operation planning and decision-making requires users to manually evaluate masses of digital data to determine the predicted outcomes of a Course of Action.
Our approach automates this process using a reasoning engine that identifies potential Courses of Action based on the behavior of enemy agents within a given environment.
Completed as part of NAVY SBIR Phase I (2021 – Present) focused on reducing manual planning and decision making processes.
Graphical abstract representing planning and decision-making tool:
Reasoning engine incorporates static and streaming data, library of courses of action, and domain-specific ontologies.
Reasoning engine predicts agent trajectories to identify enemy COAs through sequential observations and hypothesis testing.