SBIR/STTR Award attributes
MALLETS will provide a robust machine learning approach to complex, multi-vehicle EW engagements with an intelligent adversary. Through both offline and online learning, MALLETS will develop a model of the adversary’s playbook and dynamically recommend TTPs (a set of individual CoAs assigned to specific platforms) based on mission requirements and resource availability during the mission. While current approaches rely predominantly on pre-planned tactics and maneuvers, MALLETS will continually adapt TTPs as the system learns more about the adversary’s perception, capabilities, and intents. MALLETS combines a Theory of Mind (ToM) approach with in-mission perception management and adjustment, which enables greater flexibility and awareness of the adversary.
