The US DoD is committed to improving the
effectiveness of the collective set of ISR assets in generating mission
relevant information. Their vision is of a self-synchronizing, horizontally
integrated “swarm” of sensors, processing elements, and communication assets
that autonomously organize to meet the dynamically evolving ISR needs of
future missions/campaigns. This talk describes an analysis workstation that is
being constructed to support the evaluation of alternative designs for such a
system. Within the workstation a complex adaptive system models the dynamic
formation of collection teams while evolutionary algorithms, operating at the
agent level, attempt to optimize the global performance of the ISR family of
systems by modifying the various agent’s responsiveness to attributes of the
“support requests.” Joint MEASURE, a DEVS based Monte Carlo mission
effectiveness simulator developed by Lockheed Martin, provides the
infrastructure for this workstation enabling the unpredictability of scenario
evolution to be an integral element of the optimized solution. An
overview of the architecture is provided along with sample results and lessons
learned.