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All points are interconnected and interdependent, unfolding in a nonlinear manner with no central source of authority.
Early versions of systems theory assumed that systems could be 'optimized' to a single condition. CAS analysis assumes that more than one system state can satisfy optimizing criteria, and so the system is able to gravitate to multiple equilibria.
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An enslaved state can persist as an attractor (see Attractor States) within a Fitness Landscape.
Beyond its day-to-day usage, this term used in now employed in the social sciences to highlight the Path Dependency exhibited in many social systems. This is seen to contrast with prior conceptions like "the march of history", which imply a clear causal structure. By speaking about the work as something contingent, it also begs the question of what other "worlds" might have just as equally manifested, had things been slightly different.
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Pictured below: the contingent trajectory of the double pendulum:
See also: Causal loop diagram - Wikipedia
In geography there has been a move away from thinking about space as a "thing" and to instead think about how different places exist due to how they interact with flows. Places that capture more flows, are more geographically relevant
The nature of a building block varies according to the system: it may take the form of an ant, a cell, a neuron or a building.
Complex Adaptive Systems theory provides a useful lens with which to understand various phenomena. Keep reading about Complexity
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The Sierpinski Fractal shown here is a nice example of a scale-free/power law system. At each level of zoom we encounter the same pattern. Such self-similar structures follow power-law distributions of their components: that is to say, a few elements within the overall pattern are very large, but there are many more elements within the structure that become vanishingly small.
Let us take a look at another well known fractal, the Koch Curve. The Fractal demonstrates how multiple, {{timeiterative}} have the power of generating something highlighly unexpected:
First four iterations of the Koch Curve
We begin with a line and a simple three step rule protocol:
As seen in the image above, a repeated simple rule set is all that is required to generate a high level of complexity. This is the basic principle at work in creating all Fractals - where basic instructions generate an output, whose new properties (going from one line segment to four line segments), become the new context upon which to re-apply the rule.
While we can obtain a lot of richness from such phenomena, it would be incorrect to state that the resulting figure 'adapts' or 'learns' - instead it is more accurate to state that it 'unfolds' over multiple iterations.
Cite this page:
Wohl, S. (2022, 1 June). Fractals. Retrieved from https://kapalicarsi.wittmeyer.io/definition/fractals-1
Fractals was updated June 1st, 2022.
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