Neat AI does Smooth Life - the next step in Conway's Game of Life
36,396
Published 2021-09-05
Underwater shot :
• water under microscope - amoeba time ...
ShaderToy Smooth Life
www.shadertoy.com/view/XtdSDn
Github Code (Python)
github.com/duckythescientist/SmoothLife
From Wikipedia :
en.wikipedia.org/wiki/Conway%27s_Game_of_Life
The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970.[1] It is a zero-player game, meaning that its evolution is determined by its initial state, requiring no further input. One interacts with the Game of Life by creating an initial configuration and observing how it evolves. It is Turing complete and can simulate a universal constructor or any other Turing machine.
Origins
In late 1940, John von Neumann defined life as a creation (as a being or organism) which can reproduce itself and simulate a Turing machine. Von Neumann was thinking about an engineering solution which would use electromagnetic components floating randomly in liquid or gas. This turned out not to be realistic with the technology available at the time. Stanislaw Ulam invented cellular automata, which were intended to simulate von Neumann's theoretical electromagnetic constructions. Ulam discussed using computers to simulate his cellular automata in a two-dimensional lattice in several papers. In parallel, von Neumann attempted to construct Ulam's cellular automaton. Although successful, he was busy with other projects and left some details unfinished. His construction was complicated because it tried to simulate his own engineering design. Over time, simpler life constructions were provided by other researchers, and published in papers and books.[citation needed]
Motivated by questions in mathematical logic and in part by work on simulation games by Ulam, among others, John Conway began doing experiments in 1968 with a variety of different two-dimensional cellular automaton rules. Conway's initial goal was to define an interesting and unpredictable cell automaton. For example, he wanted some configurations to last for a long time before dying and other configurations to go on forever without allowing cycles. It was a significant challenge and an open problem for years before experts on cellular automata managed to prove that, indeed, the Game of Life admitted of a configuration which was alive in the sense of satisfying von Neumann's two general requirements. While the definitions before the Game of Life were proof-oriented, Conway's construction aimed at simplicity without a priori providing proof the automaton was alive.
Conway chose his rules carefully, after considerable experimentation, to meet these criteria:
There should be no explosive growth.
There should exist small initial patterns with chaotic, unpredictable outcomes.
There should be potential for von Neumann universal constructors.
The rules should be as simple as possible, whilst adhering to the above constraints.[2]
The game made its first public appearance in the October 1970 issue of Scientific American, in Martin Gardner's "Mathematical Games" column. Theoretically, the Game of Life has the power of a universal Turing machine: anything that can be computed algorithmically can be computed within the Game of Life.[3][4] Gardner wrote, "Because of Life's analogies with the rise, fall and alterations of a society of living organisms, it belongs to a growing class of what are called 'simulation games' (games that resemble real-life processes)."[5]
Since its publication, the Game of Life has attracted much interest because of the surprising ways in which the patterns can evolve. It provides an example of emergence and self-organization. Scholars in various fields, such as computer science, physics, biology, biochemistry, economics, mathematics, philosophy, and generative sciences, have made use of the way that complex patterns can emerge from the implementation of the game's simple rules.[citation needed] The game can also serve as a didactic analogy, used to convey the somewhat counter-intuitive notion that design and organization can spontaneously emerge in the absence of a designer. For example, philosopher Daniel Dennett has used the analogy of the Game of Life "universe" extensively to illustrate the possible evolution of complex philosophical constructs, such as consciousness and free will, from the relatively simple set of deterministic physical laws which might govern our universe.[6][7][8]
Rules
Generative Art,AI,A.I.,neural Net,using Python,python,tutorial,processing,p5js,coding,speedrun,blender,after effects
All Comments (21)
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Really liked the concept of the video, but having the real life amoebas in the background made it difficult to see what was happening.
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It's difficult to differentiate the simulation from the animated background, and that difficulty puts into question the merit of what is being observed.
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Wait, I'm a glider now??? =]
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love this channel. this episode combines many of my interests. woot.
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I'd like to see different cell "types". There's only so much you can do in a two-state simulation.
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Is the course correction caused by floating point rounding? I assume there's a lot of strangeness associated with that.
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Love the video. Appreciate being pointed in the direction of how to do it myself!
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I love this channel, I'm surprised it doesn't have more subs
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This channel is amazing. Absolutely love it.
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I am so excited for this after your experiment with "Game of Life". So much thanks.
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These creatures are fascinating. It seems like they tend towards all dying out, maybe it would be interesting to periodically sprinkle in "food" for them to consume, to continue their lives.
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Keep up the good work. This channel will get huge soon ;)
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Hopefully, in a few years this would evolve into three dimensions.
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The cell division emerging from this is mind blowing
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Woah, that looks soo cool!
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Hypnotic.
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inspirational work, set me off on a lovely coding tangent...
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Ok, how did i end up here
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This playlist is fantastic. I wondered if there’s any chance we could chat about this privately?
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Very nice video! But a bit of background and explanation of what is going on on the screen and what are the rules of the simulation would have been nice.
