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Most of the grand challenges of humanity today involve complex agent-basedsystems, such as epidemiology, economics or ecology. However, remains as apending task the challenge of identifying the general principles underlyingtheir self-organizing capabilities. This article presents a novel modelingapproach, capable to self-deploy both the system structure and the activitiesfor goal-driven agents that can take appropriate actions to achieve theirgoals. Humans, robots, and animals are all endowed with this type of behavior.Self-organization is shown to emerge from the decisions of a common rationalactivity algorithm, based on the information of a system-specific goalsdependency network. The unique self-deployment feature of this approach, thatcan also be applied to non-goal-driven agents, can boost considerably the rangeand depth of application of agent-based modeling.

Ants, robots, humans: a self-organizing, complex systems modeling approach