Battlefield Learning

Battlefield Learning (BL) is the process of understanding what is observed (enemy & own actions) in the command center and correctly adapting our actions to lead to a positive outcome. The character of BL is the coherent union of man & machine that will best provide adaptability to off-nominal and evolving missile threats. Battlefield Learning will largely take place in exercises that prepare operators for a short but potentially destructive war. Human/machine interaction is where today’s C2BMC BL lies. The challenge is to find a meaningful way to measure “good” Human-in-Loop (HIL) C2BMC interaction and learning and to create BL algorithms to advise the HIL in a way that best promotes human sense making in uncertain environments. The Phase I effort established a framework called the Work-Centered Intelligent-Agent System (WIS) for BL. The three components of the WIS are 1) the real-time results of current C2BMC algorithms, 2) the work centered interface that communicates the algorithm’s results in a way that promotes human sense making, and 3) an association algorithm that captures the “general” behavior of C2BMC algorithms and the behavior of HIL operators. The Phase II effort will complete and deploy the WIS at the C2BMC-X laboratory.