To provide effective communication and coordination training to Remotely Piloted Aircraft (RPA) crewmembers, we propose a prototype adaptive training communication environment using our T-BORG simulation and integration framework to incorporate new and pre-existing intelligent agents and synthetic teammates at various levels of fidelity. The problem addressed is that simultaneous monitoring of multiple mIRC chat windows creates a potential for high workload, and the resulting asynchronous communication impacts coordination. These coordination breakdowns can, in turn result in the loss of a high-valued target or a failure to detect an emerging threat. Our system will address this by allowing multiple entities to interact in a complex, time sensitive scenario. Phase I will deliver a prototype system that demonstrates an adaptable architecture that simulates multiple chat windows, monitors performance, and increases the chat workload in response to this performance. The system will initially draw upon CERIs UAV-STE but will be designed to connect to a number of simulation environments. Phase II will incorporate higher fidelity analytic and behavior subprograms with provision for substitution or addition of other code.
Keywords: Pmats, T-Borg, Mq-1 Predator, Mirc, Behavioral Intelligence, Certt, Remote Crew Training
