The Mandelbrot set (M set) is a particular mathematical set of points whose boundary is a distinctive and easily recognizable two-dimensional fractal shape.
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The set is closely related to Julia sets (which include similarly complex shapes), and is named after the mathematician Benoit Mandelbrot, who studied and popularized it.
The M. set is not unique in the spontaneous emergence of structure—the same thing has been discovered in other mathematical systems such as cellular automata, neural networks, simulations of group behaviour, and boolean networks.
Stuart Kauffman calls it "order for free", because it is not evident in the defining equations.
Studying boolean networks, Kauffman has even identified general parameter values that virtually ensure order will emerge, even though the only way to find out what that order looks like is to calculate it out.
Take one example.
Take one example.
The cellular automaton called "Langton's Ant" couldn't be any simpler.
Imagine an ant crawling on a grid where each square must be either black or white.
If the ant lands on a black square, he colors it white and turns right.
If he lands on a white square, he colors it black and turns left.
The ant wanders aimlessly about patterning and repatterning the plane, until at some point, depending on the initial setup, something very strange happens: the ant begins building a "highway" out to infinity.
Numerous computer trials confirm that this happens no matter what the initial setup, yet this is an empirical fact only.
It is probably impossible to prove it analytically.
In other words, the only reason or explanation for "Why does the ant build a highway every time" i
Because it is true for setup A , setup B, setup C, . . . which is really no explanation at all.
Such an explanation amounts to, "Because it does."
As with the M. set, we have a complete reductionistic explanation of the ant's every move
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Yet it tells us nothing about the large-scale structure.
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In other words, nothing in the simple defining equations of Langton's Ant would indicate that highway-building behavior will result.
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There is no finite explanation.
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Yet it tells us nothing about the large-scale structure.
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In other words, nothing in the simple defining equations of Langton's Ant would indicate that highway-building behavior will result.
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There is no finite explanation.
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Yet it happens just the same!
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There is no simpler "why".
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It just is.
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Neither, therefore, can we be certain that highway-building always happens.
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We could demonstrate it for a billion starting set ups, but it could fail for the billion-and-first.
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Analogous situations are ubiquitous in the world of cellular automata and related fields.
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Leading researchers such as Stephen Wolfram to advocate a "new kind of science" based on empirical discovery and not analytic proof.
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Since science is about understanding the world, what they are advocating is really a new conception of understanding, one which is no longer subject to certainty.
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It becomes necessary to accept that complex systems have emergent properties for which we will never find a reductionistic "why".
Yet it happens just the same!
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There is no simpler "why".
.
It just is.
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Neither, therefore, can we be certain that highway-building always happens.
.
We could demonstrate it for a billion starting set ups, but it could fail for the billion-and-first.
.
Analogous situations are ubiquitous in the world of cellular automata and related fields.
.
Leading researchers such as Stephen Wolfram to advocate a "new kind of science" based on empirical discovery and not analytic proof.
.
Since science is about understanding the world, what they are advocating is really a new conception of understanding, one which is no longer subject to certainty.
.
It becomes necessary to accept that complex systems have emergent properties for which we will never find a reductionistic "why".
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In other words reductionism has increasing limitations.
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Limitations that mean that it's time has passed as a way of understanding.
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Time to move on.
In other words reductionism has increasing limitations.
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Limitations that mean that it's time has passed as a way of understanding.
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Time to move on.
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