cas/definition/feature.php (core concept)
Diagram: Self-Organization


Self-organization refers to processes whereby coordinated patterns or behaviors manifest in a system without the need for top-down control.

A system is considered to be self-organizing when the behavior of elements in the system can, together, arrive at a globally more optimal functional regimes compared to if each system element behaved independently. This occurs without the benefit of any controller or director of action. Instead, the system contains elements acting in parallel that will gradually manifest organized, correlated behaviors: Emergence.

Emergent  behaviors become organized into a regular form or pattern. Furthermore, this pattern has properties that do not exist at the level of the independent elements - that is, there is a degree of unexpectedness or novelty in what manifests at the group level as opposed to what occurs at the individual level.

An example of an emergent phenomena generated by self-organization is flock behavior, where the flock manifests an overall identity distinct from that of any individual bird.

Characterizing 'the self' in 'Self'-organization

Let us begin by disambiguating self-organizing emergence from other kinds of processes that might also lead to global, collective outcomes.

Example - Back to School:

Imagine you are a school teacher, telling your students to form a line leading to their classroom. After a bit of chaos and jostling you will see a linear pattern form that is composed of individual students. At this point, 'the line' has a collective identity that transcends that of any given individual: it is a collective manifestation with an intrinsic identity (don't cut in the line!).  The line is created by individual components, expresses new global properties, but it's appearance is not the result of self-organization, it is the result of a top-down control mechanism.

Clearly 'selves' organize in this example, but not in ways that are 'self-organizing'.

Now imagine instead that you are a school teacher wanting the same group of students to play a game of tug-a-war in the school gym. Beginning with a blended room of classmates, you ask the students to pick teams. The room quickly partitions into two collectives:  one composed entirely of girls and the other entirely of boys. As a teacher, you might not appreciate this self-organization, and attempt to exert top-down control in an effort to balance team gender. What is interesting about this case is that it does not require any one boy calling out 'all the boys on this side', or any one girl doing the same: the phenomena of 'boys versus girls' self-organizes.

In the example above, we can well imagine the reasons why school teams might tend to partition into 'girls vs boys' even without explicit coordination (of course these dynamics don't always appear, but I am sure the reader can imagine lots of situations where they do).

Here, there are slight preferences (we can think of these as differentials), that generate a tendency for the elements of the system to adjust their behaviors one way vs another. In the case of the school children, the tendencies of girls to cluster with girls manifests due to tacit practices: friends cluster near friends, and as clusters appear students switch sides to be nearer those most 'like' them. Even if an individual child within this group has no strong preference - is equally friends with girls and boys - the pressures of patterns formed by the collective will tend to tip the balance. One girl alone in a team of boys will register that their behavior is non-conforming and feel pressured to switch sides, even if this is not explicitly stated.

Here there are 'selves' with individual preferences, but global behaviors are tipped into uniformity by virtue of slight system differences that tend to coordinate action.

Conscious vs unconscious self-organization:

While the gym example should be pretty intuitive, what is interesting is that there are many physical systems that produce this same kind of pattern formation but that do not require social cues or other forms of intentional volition. Instead, self-organization occurs naturally in a host of processes. Whether we are talking about schools of fish, ripples of wind-blown sand, or water molecules freezing into snowflakes, self-organization leading to emergent global features is a ubiquitous phenomena.

While the features of self-organization manifest differently depending on the nature of the system, there are common dynamics at play regardless of system. Agents in the system participate in a shared context wherein there exists some form of differential. The agents in the system adjust their behaviors in accordance with slight biases in their shared context and these adjustments, though initially minor, are then amplified through reinforcing feedback that cascades through the system. Finally an emergent phenomena can be recognized.


Let us consider the sound of cicadas chirping:

cicadas chirping in sync

The cicadas chirp in a regular rhythm. There is no conductor to orchestrate the beat of the rhythm, no head cicada leading the chorus, no one in charge. The process by which the rhythm of sound (an emergent phenomena) manifests is governed purely by the mechanism of self-organization. Let us break down the system:

  1. Agents: Chirping Cicadas
  2. Shared Context: the acoustic environment shared by all cicadas
  3. Differential: the timing of the chirps
  4. Agent Bias: adjust chirp to minimize timing differences with nearby chirps
  5. Feedback: As more agents begin to chirp in more regular rhythms, this reinforces a rhythmic tendency, further syncing chirping rhythms.
  6. Emergent Phenomena: Regular chirping rhythm.

Even if all agents in the system start off with completely different  (random) behaviors, the system dynamics will lead to the coordination of chirping behaviors.

For another example of the power of self-organization, consider this proposition: You are tasked with getting one thousand people to walk across a bridge, with their movements coordinated so that their steps are aligned in perfect rhythm. You must achieve this feat on the first try (with a group of strangers of all ages who have never met one another).

It is difficult to imagine this top-down directive ending in anything other than an uncoordinated mess. But place people on the Millennium bridge in London for its grand opening and this is precisely what we get:

as the video progresses, watch the movement of people fall into sync

There are a variety of mechanisms that permit such self-organization to occur. In the millennium bridge video, the bridge provides the shared context or environment for  the walkers (who are the agents in the system). As this shared context sways slightly (differential) it throws each agent just a little bit off balance (feedback).  Each individual then slightly adjusts their stance and weight to counteract this sway (agent bias), which serves only to reinforces the collective sway direction. Over time, as the bridge sways ever more violently, people are forced to move in a coordinated collective motion (emergence) in order to traverse the bridge.

What is important to note in this example is that we do not require the agents to agree with one another in order for self-organization to occur. In our earlier example - that of school children forming teams - we can imagine that a variety of factors are at work that have to do with active volition on the part of the children. But in the example above, movement preferences have nothing to do with observed walking behavior or individual preferences. Instead, the agents have become entangled with their context (which is partially formed of other agents), in ways that constrain their movement options.

Enslaved Behavior

Accordingly, in self-organizing systems agents that might initially possess a high number of possible states that are able to enact (see also Degrees of Freedom) the possible range of freedom becoming increasingly limited, until such time as only a narrow band of behavior is possible.

Further, while the shared context of the agents might initially be the source of difference in the system (with difference gradually being amplified over time), in reality the context for each agent is a combination of two aspects: both the broader shared context (the bridge) and the emerging behaviors of all the other agents within that context. This is to say that once a global behavior emerges, subsequent self-organization of the agents is constrained by the emerged context agents are also a part of.

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Cite this page:

Wohl, S. (2022, 30 May). Self-Organization. Retrieved from

Self-Organization was updated May 30th, 2022.

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In Depth: Self-Organization

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Inside the ant colony - Deborah M. Gordon

View full lesson: Ants have one of the most complex social organizations in the animal kingdom; they live in structured colonies that contain different types of members who perform specific roles. Sound familiar? Deborah M. Gordon explains the way these incredible creatures mate, communicate and source food, shedding light on how their actions can mimic and inform our own behavior.

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Segregation model

Economist who developed one of the first cellular automata demonstrations: showing how segregation of agents will emerge as a phenomena due to simple rules that, in and of themselves, do not appear to be strongly linked to segregation outcomes.

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Santa Fe Institute; Fitness Landscape

Major complexity theorist associated with the Sante Fe institute, developed idea of a Fitness Landscape

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John Holland is considered one of the seminal thinkers in Complex Adaptive Systems theory.

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Synergetics | Enslaved States

Haken popularized the concepts of Enslaved States and 'synergetics'. The notion of 'enslavement' is similar to the idea of Attractor States, wherein a system will tend to gravitate towards a particular regime and then remain in that state unless there is a system Perturbation.

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An evocative example of emergence found in simple agents such as birds, ants, or fish.

Relates to {{bottom-up-agents}}

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A concept from Deleuzian philosophy - when distinct entities settle into synergies and act as a unit.

Relates to {{Assemblage-Geography}}

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A regime of particular fitness that an agent can occupy.

Fitness ‘peaks’ are regimes wherein a given agent behavior maximizes energetic returns while minimizing outputs. Peaks are thus optimum behaviors in phase space - though there may be numerous peaks, each employing different strategies. See also {{Fitness-Landscape}} Learn more →

Emergent states often constrain  the agents that initially formed that state.

An enslaved state can persist as an attractor (see Attractor States) within a Fitness Landscape.

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From: Ants! Natures Secret Power

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Sole & Goodwin

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Camazine, Deneubourg, Franks, Sneyd, Theraulaz, Bonabeau

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Complex Adaptive Systems become more 'fit' over time. Depending on the system, Fitness can take many forms,  but all involve states that achieve more while expending less energy.

What do we mean when we speak of Fitness? For ants, fitness might be discovering a source of food that is abundant and easy to reach. For a city, fitness might be moving the maximum number of people in the minimum amount of time. But fitness criteria can also vary - what might be fit for one agent isn't necessarily fit for all.

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Complex Systems can unfold in multiple trajectories. However, there may be trajectories that are more stable or 'fit'. Such states are considered 'attractor states'.

Complex Adaptive Systems do not obey predictable, linear trajectories. They are "Sensitive to Initial Conditions", such that small changes in these conditions can lead the system to unfold in unexpected ways. That said, in some systems, particular 'potential unfoldings' are more likely to occur than others. We can think of these as 'attractor states' to which a system will tend to gravitate.

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There would be some thought experiments here.

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