Modeling Synergies in Large Human-Machine Networked Systems

Network centric military systems (NCW) are planned to involve hundreds to thousands of manned and autonomous entities cooperating to achieve complex joint objectives in incomplete information environments. While in today’s military tight automated coordination exists within isolated, stovepiped systems most information and instruction still passes through a human chain of command. Benefits from pervasive networking are expected to result in enabling an increased pace of coordinated activity and reactivity among forward forces. By sensing, communicating, and acting locally rather than sending information up and down the hierarchy, forces are expected to be able to coordinate their actions laterally to take advantage of local and rapidly changing situations. Traditional human roles will need to be adapted to fit the new NCW architecture. The quantities of peer-to-peer information available at the edge of the network will be much greater than those currently handled by filtering and aggregating up the hierarchy and likely beyond the cognitive capabilities of a human. Conversely, with decision making and cooperation occurring at the edge outside of the conventional chain of command, new mechanisms may be needed for conveying the commander’s intent and assessing progress on the battlefield. In both cases research is needed to identify potentially beneficial or damaging emergent effects. The proposed research will be mathematically based drawing on human data and models as necessary to accurately characterize their behavior within the system.