In a few years, the National Training Center (NTC) will have new simulation systems and upgrades to RDMA and RMCS. Given effective and efficient integration, tehse systems will increase, significantly, the amount and fidelity of data available to the training analyst. How effective these improvements are depends on how efficiently the man-machine combinations at training analyst work stations are able to collect, analyze, package, and distribute the desired performance data. In Phase I, we will conduct functional requirements analyses of each step of a proposed concept; investigate the feasibility of advanced processing and decision aid techniques; and develop a taxonomy that technically, as well operationally, will lead to automated integration of the data collected from simulation, observation (human and television) and instrumentation, and the application of decision aid functionality for organizing and analysing the real time training performance data. In phase ii, we will transition the taxonomy into its total capability context. We will design, model and implement the Phase I approach in sufficient detail to demonstrate the feasibility of the data collection and analysis concept.
Keywords: Artificial Intelligence Automation Decision Aids Distributed Processing Combat Training Centers