Self-organizing systems-of-systems offer the possibility of autonomously adapting to new circumstances and tasking. This could significantly benefit large endeavors such as smart cities and national defense by increasing the probability that new situations are expediently handled. Complex self-organizing behaviors can be produced by a large set of individual agents all following the same simple set of rules. While biological rule sets have application in achieving human goals, other rules sets may be necessary as these goals are not necessarily mirrored in nature. To this end, a set of system, rather than biologically, inspired rules is introduced and an agent-based model is used to simulate and analyze the behavior produced with various parameters. Agents represent systems and their decisions are defined by the given rule set and parameters. The environment provides a variety of time-critical missions on an ongoing basis. The effectiveness of a particular rule or set of rules is measured by a set of key performance metrics such as the rate at which missions achieve their required capabilities within a given deadline and the average time required to do so. Different rules will be compared using this criterion along with an assessment of their ability to demonstrate beneficial self-organizing behavior
