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Complex Networks, Simple Rules: Life, The Universe and Everything!
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More videos and papers about these systems are:
Complex Networks, Simple Rules
Searching For Complex Systems - Live
Complex Network Growth And Chaos From A Simple Rewrite Model
Complex Networks from Simple Rules (paper)
Explore the systems online with Wolfram Demonstrations
In this videos I try to explain some of the reasons I am so interested in the dynamics of network rewrite systems (that generate complexity via simple rules).
I discuss the systems using my first ever 3D printed shapes -the complex network grown up to step 300, and the hyperbolic network grown up to time step 900.
Looking at these kind of toy models can teach us lots of interesting things about emergent properties, such as -when and where are the most complex parts of the universe expected to be observed.
The systems are also interesting from a topological viewpoint, since they both begin with a cube (a planar graph), and quickly become non-planar. In fact, if one things of the systems as an evolving surface then one can literally see the formation of things like cross-caps which stop the system being orientable.
More importantly, the unpredictability of these systems teaches us to expect unpredictability in the life evolution of individual biological organisms, species, and the entire universe.
We also discuss how such systems could be used to model memory, be having the structure represent a neural network, while the writer's position represents the place the thinker is focused upon.
We show how the network grows after the first 300 time steps and use 3D (rotatable) graphics to show the intricate network developed after 100000 time steps.
The question of whether this system ever falls into a repetitive growth pattern may well be undecidable.
Many of my works an videos are inspired by Stephen Wolfram's `A New Kind Of Science'
By looking at the other programs of this type collected on my website, one can find many systems which exhibit chaos emergence and, which can model the growth of many biological organisms (e.g., plants).
The other `curly rule' produces a non-planar network (corresponding to a non-trivial topological surface), and essentially this network corresponds to hyperbolic space.
This is more evidence for the wide range of difference spaces/geometries that can be made by these systems,
Complex Networks, Simple Rules
Searching For Complex Systems - Live
Complex Network Growth And Chaos From A Simple Rewrite Model
Complex Networks from Simple Rules (paper)
Explore the systems online with Wolfram Demonstrations
In this videos I try to explain some of the reasons I am so interested in the dynamics of network rewrite systems (that generate complexity via simple rules).
I discuss the systems using my first ever 3D printed shapes -the complex network grown up to step 300, and the hyperbolic network grown up to time step 900.
Looking at these kind of toy models can teach us lots of interesting things about emergent properties, such as -when and where are the most complex parts of the universe expected to be observed.
The systems are also interesting from a topological viewpoint, since they both begin with a cube (a planar graph), and quickly become non-planar. In fact, if one things of the systems as an evolving surface then one can literally see the formation of things like cross-caps which stop the system being orientable.
More importantly, the unpredictability of these systems teaches us to expect unpredictability in the life evolution of individual biological organisms, species, and the entire universe.
We also discuss how such systems could be used to model memory, be having the structure represent a neural network, while the writer's position represents the place the thinker is focused upon.
We show how the network grows after the first 300 time steps and use 3D (rotatable) graphics to show the intricate network developed after 100000 time steps.
The question of whether this system ever falls into a repetitive growth pattern may well be undecidable.
Many of my works an videos are inspired by Stephen Wolfram's `A New Kind Of Science'
By looking at the other programs of this type collected on my website, one can find many systems which exhibit chaos emergence and, which can model the growth of many biological organisms (e.g., plants).
The other `curly rule' produces a non-planar network (corresponding to a non-trivial topological surface), and essentially this network corresponds to hyperbolic space.
This is more evidence for the wide range of difference spaces/geometries that can be made by these systems,
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