Modern battle scenarios involve a huge amount of data and information. According to Wikipedia:
“Network-centric warfare, also called network-centric operations or net-centric warfare, is a military doctrine or theory of war pioneered by the United States Department of Defense in the 1990s.
It seeks to translate an information advantage, enabled in part by information technology, into a competitive advantage through the robust networking of well informed geographically dispersed forces. This networking—combined with changes in technology, organization, processes, and people—may allow new forms of organizational behavior.
Specifically, the theory contains the following four tenets in its hypotheses:
- A robustly networked force improves information sharing;
- Information sharing enhances the quality of information and shared situational awareness;
- Shared situational awareness enables collaboration and self-synchronization, and enhances sustainability and speed of command; and
- These, in turn, dramatically increase mission effectiveness.”
Now that complexity can be measured in real-time using the QCM engine OntoNet, we can take things to the next level: Complexity-Centric Warfare. The first step is to map the entire information flow obtained from a multitude of sensors onto a Complexity Map (before the enemy can trigger an EMP!). The map evidently changes in time as the battle evolves. The concept is illustrated below.
Clearly, sensors gather data about all the forces involved in a particular scenario. The combined map, showing two opposing forces, is illustrated below (clearly, an extremely simple example is shown). Experiments in Air Traffic Control conducted by Ontonix show that it is possible to track hundreds of airborne objects using radar and in real-time. A Massively Parallel Processing version of OntoNet (currently under development) will allow to process thousands of objects.
Once the maps are established, two issues of tactical character become evident:
- Concentrate firepower on enemy hubs.
- Protect your own hubs.
Hubs are easily identified once a Complexity Map is available. A more sophisticated target ranking approach is based on battle Complexity Profiling, which allows to ranks the various actors based on their footprint on the entire scenario. Clearly, just as a Complexity Map changes with time so will the Complexity profile.
And now to strategic issues. How to manage a battle using complexity? Simple. Fast scenario simulation technology provides numerous options to chose from. And how do you chose between, say, two very similar options? You take the one with lower complexity. In other words, you try to steer the conflict in a way that reduces its complexity. The concept is illustrated below.
A less complex battle scenario is easier to manage. It is easier to comprehend.It allows for faster decision-making. It is easier to be more efficient in a less complex situation than a highly complex one. Finally, highly complex situations have the nasty habit of suddenly delivering surprising behavior. And in the worst possible moment. Sounds like one of Murphy’s laws.