Complexity Theory, Chaos, Self-Organization, and Ants

When I was in elementary school I used to be obsessed with ants. During the spring they would come and swarm our kitchen and raid our refrigerator. While my parents mostly ignored them, setting out traps for them and calling it a day, I would watch them and how they behaved. While my own behavior can be understood as me having nothing better to do on a Tuesday afternoon, theirs seemed much harder to comprehend. Sure they were after food, but why our house? What compelled them to enter our house and how did the rest of the colony know where our fridge was and where our food was stored? These questions, put on hold for several years, were revived by the emergence of an idea of complexity theory.

Complexity theory analyzes the associations between systems and their interactions. Through the study of these systems patterns and structure become apparent. Independent agents within the system are understood as being parts of a coherent system which can, in turn, be better understood overall. Ideas within complexity theory which will be used to understand the actions of ants are: chaos, and self-organization.

Chaos within complexity theory describes how small differences in initial conditions of the system can lead to large outcomes to the system’s overall trajectory. This is most commonly understood through the butterfly effect, but it also extends to the behaviors of ants. As a colony establishes itself, scouts are sent out to determine the locations of food and water. Once a scout makes contact with a potential source of sustenance, they return to the colony. As they make their return trip they leave a trail of pheromones that allows future ants to follow the route to the food source (see figure 1). Workers then follow this pheromone trail to the food/water and proceed to collect it, bringing it back to the colony. This whole process is an example of chaos at work, as the actions of individual scouts during the initial conditions of the colony lead to ants in my fridge and an infestation in the kitchen.

Self-organization is often understood as to operate in conjunction with chaos, but the difference between these two aspects is that self-organization is more focused on changes within the system. An ant finding leftover pizza in the fridge is very dependent on external conditions, and would fall under the aspect of chaos. A queen ant dying and the colony collapsing is an example of change within the system and would serve as an example of self-organization (see figure 2). While the collapse of order within the colony system may be observed, this nature is very much part of how the ant colony is organized. This change in the conduct of the system carries over and effects the conduct of individuals.

Through the observation of ants, complexity theory and its components can be better understood. The system which is the colony is naturally a good example to see how the actions of individuals within and without can effect the trajectory of the system. It also helps to explains why ants one day are stealing leftovers and the next have disappeared.

Figure 1: Scout ants creating pathways from the colony to a food source
(Sempo, Grégory, et al. “Fig. 2. Trail Recruitment in Ants. An Ant Scout (in Black) Which Has…” ResearchGate, 1 Aug. 2018,
Figure 2: An example of a queen ant dying and the colony system collapsing
(Belam, Martin. “Museum Posts ‘Queen Has Died’ Notice to Explain Vanished Ant Colony.” The Guardian, Guardian News and Media, 19 Oct. 2016,

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