The Game of Life

Emergence in Generative Art

Complex Worlds From simple rules

This online exhibition is in part a tribute to the mathematician John Horton Conway who recently passed away from COVID-19. Among Conway’s many gifts to the world was his famous “Game of Life” popularized in a 1970 article in Scientific American. The game uses four simple rules to create a seemingly infinite amount of complex behavior and visual patterns. Conway’s work on cellular automata along with others like Stephen Wolfram has been inspirational for many of this generations most talented Generative Artists. This exhibition explores how complex visual systems can emerge from relatively simple algorithms to create art than can reframe the way we see the world. For this show, we have included four generative artists: Jared Tarbell, Alexander Reben, Kjetil Golid, and Manolo Gamboa Naon. We will hear from each of them in a series of interviews to be released over the next several weeks.

Manolo

Alexander Reben

Jared Tarbell

Kjetil Golid

The Game of Life is an example of cellular automation, a collection of black and white squares, or "cells'' on a grid, that evolve through several steps according to a set of rules. These very basic rules trigger astonishing behaviors, so unpredictable and so complex that they can make a small set of black and white squares on a grid appear to "come to life." This unpredictable and complex behavior is called emergence.

Emergence happens when small things form bigger things that have different properties than the sum of their parts. What does that mean? Think of an ant colony. Each ant is pretty dumb, defenseless, and guided by basic rules. But when combined with hundreds of other ants in a colony, a new intelligence emerges at the colony level that allows them to adapt, defend themselves, and find food. These properties or behaviors emerge when the smaller parts interact in a larger system. And this larger system, the colony, appears to have higher intelligence than the sum of its parts would imply. The world is full of examples of emergence. Think of a flock of birds flying through the air in an intricate flight pattern. How do they avoid hitting each other? Is there a leader bird telling them which way to go? The flock's complex behavior emerges from each bird following a few basic rules at the individual or local level. Intelligence is decentralized across the flock, and simple actions locally (individual birds) produce complex behaviors globally (the flock level).

We, as humans, are examples of emergent behavior. Atoms form molecules that form proteins that form cells that form organs that form humans, which form societies. Atoms and molecules are not all that complex or smart on their own, but they can combine following simple rules to make highly intelligent human beings. Emergence is not limited to natural phenomena. Our economy is an emergent system, as it has attributes outside the control of any single human.

So what does emergence have to do with generative art? When artists program a large number of entities on a computer screen to follow basic rules and interact with each other, intricate lifelike patterns emerge. These artists are not creating images of our world, but instead, programming rules for producing their own worlds, complete with emergent behaviors. While we doubt John Conway considered himself an artist, his Game of Life is itself an emergent system and has inspired many generative artists do to the complexity it can produce from relatively few rules. Instead of ants in an ant colony, Conway has squares on a grid. Like ants, the squares are simple and only have two states: "live" or "black" and "dead" or "white." The squares can establish if the eight neighboring squares surrounding are "living" or "dead," as well.Depending on that information, each square then changes or stays the same based on Conway's famous four rules:

Any live cell with fewer than two live neighbors dies, as if caused by underpopulation.
Any live cell with two or three live neighbors lives on to the next generation.
Any live cell with more than three live neighbors dies, as if by overpopulation.
Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.

You set the game up by selecting some squares on the grid to start as "living." Once you run the code, the network animates based on the execution of Conway's rules above. Below is an example of the Game of Life on a relatively small grid.

The work below, created by Alexander Reben, was inspired by Conway’s Game of Life and follows his four basic rules across a much larger grid.

The Game of Life is sometimes called a "Zero Player" game, in that once you set up the starting position and run the code, the game plays out on its own. However, even small changes in selecting which squares start as "alive" can dramatically impact how the animation plays out. By playing with the initial configuration and manipulating the scale of the board, as well as adding additional rules to the game, artists can improvise on the core of the game and create mesmerizing new artworks. The same way one hundred artists can paint the same motif and produce wildly different paintings, generative artists can program work inspired by the same algorithms and produce equally varied results.

In the artworks here, artist Alexander Reben plays with the rules of the Game of Life on a much larger field. For the second example, Reben has also added new rules that change the colors of the squares. The results are like a mix between a stop-motion video of flowers blooming in a garden and an intergalactic shootout between alien spaceships. You might think a work like this would take a massive set of instructions because there are so many moving parts that go on for a long time without ever repeating.

That is the power of emergent behavior. The few short lines of code below actually capture all of the instructions needed to produce the work above. You can even try it yourself - simply copy the code below and paste it into your browser.

data:text/html,<canvas id="S" style="height:97vh"></canvas><script>SEED=1234567,C=S.getContext("2d"),S.width=S.height=W=500,m=2147483647,R=()=>(SEED=48271*SEED%m)/m,I=C.createImageData(W,W),g=Array.from({length:W},()=>Array.from({length:W},()=>0|2*R())),p=Array(W).fill().map(()=>Array(W)),setInterval(()=>{for(C.putImageData(I,0,0),j=1;j<W-1;j++)for(k=1;k<W-1;k++){for(t=0,u=-1;2>u;u++)for(v=-1;2>v;v++)t+=g[j+u][k+v];t-=g[j][k],p[j][k]=0===g[j][k]?3==t?1:0:2==t||3==t?1:0}for(g=p.map(d=>({...d})),j=0;j<W;j++)for(k=0;k<W;k++)i=4*(j+k*W),I.data[i+3]=255,a=i+1,b=i,c=i+2,u=I.data[a],v=I.data[b],w=I.data[c],g[j][k]?(I.data[a]=255,I.data[b]=255):8<u?I.data[a]=u-8:4<v?(I.data[b]=v-4,128>v&&(I.data[c]=255)):8<w&&(I.data[c]=w-8)},33);</script>

Pretty awesome, right? That tiny amount of code contained Conway's complete set of rules (plus some additional conditions added by Reben). It was capable of producing an artwork that slowly unfolded over time with vivid visual detail and evolving lifelike motion and interactions.

Reben's background is in applied math and robotics, and his work is about the relationship between humanity and technology -- specifically, psychology and engineering. Since elementary school, he has been coding, and the aspect of code he always found intriguing is its ability to do seemingly magical and beautiful things purely through logic. Reben's thesis at MIT Media Lab focused on a robot he developed called Boxie. Boxie could only perform simple actions, but when you put all of those actions together, Boxie appeared to be alive and intelligent. Boxie relates to Conway's Game of Life in that the actual programming and sensors required to make it appear alive were quite simple. Obviously, neither Boxie nor the Game of Life is alive. However, there is something in our psychology that makes us think that they could be. As Reben explains:

‘Conway's Game of Life is more like half psychology and half math. We, as humans, are interpreting the actions of these pixels as having agency of some sort. We are picturing them as alive. Algorithms are only part of it. It is a human algorithm because it is our interpretation of what it is doing. I think that also plugs into viewing art. A lot of art is about how we interpret it in our own context. I bet a dog would interpret Conway's Game of Life differently than we do.’

We will dive much deeper into Reben's fascinating work and share our full interview in the coming weeks. Let's take a look at how another generative artist interprets Conway's Game of Life.

Artist Manolo Gamboa Naon from Argentina is one of the most talented and prolific generative artists working today. He puts out work almost daily without ever repeating himself, and his images confound and surprise even the most experienced and skilled computer programmers. For his interpretation of the Game of Life, he layered several versions of the game playing out simultaneously, giving the illusion of depth and increasing its visual intricacy and dynamism. As Manolo explains: '

‘I love when simple rules become really complex ... I feel that they even explain the world in a very reduced way. The videos that I made are several layers of Game of Life with different sizes. At first, I wanted to explore the patterns that remain static, live for a while, and reach a point where they do not mutate anymore ... and disappear with time, and new ones appear. I made this work a video because it seems that time is an essential element in the Game of Life. Initially, I thought to use Game of Life to find interesting images (there are aspects that remind me of a lot of pixel art -- I can't stop seeing characters from Space Invaders). But ultimately, I think "life" appears with movement/evolution/time. So I liked the idea of having two moments. First, they evolve and come alive, and then they die and disappear, and in time others are born, on and on like this forever.’

You may think that if artists are using similar rules or algorithms and writing code that executes the same way each time, there cannot be too much room for surprises or accidents. You would be wrong. Generative art typically unfolds not unlike a painting or a sculpture, where the artist is learning, discovering, and adapting to the work as mistakes and surprises emerge. In this earlier interview, he explains the importance of accidents and surprises in his work:

‘After a certain point, I believe that the maturity of my style was formed by making small errors because I was discovering as I went along. From these errors, I take an idea, and it stays. I learn how to manipulate these errors. The error is central to the work of generative artists apart from, obviously, the rules, and the rules become a text that converts into an image. It is impossible to have what you imagine become what you see. The beginning is errors, errors, errors, errors. They are beautiful errors.’

Beautiful errors indeed, Manolo's work is visually stunning, with extraordinary skill and attention paid to composition and color.

The Game of Life is only one particular kind of cellular automata. It is unique in that it is two-dimensional and unfolds frame by frame over time, producing what looks like an animation. Unlike the Game of Life, one dimensional (or elementary) cellular automata are designed based on rows.

We hope art lovers with less exposure to generative art can also start to see the connection between algorithms & computation and the natural world. Tools, computers, and machines are not a threat to the natural beauty and humanity found in art -- and in the skilled hands of generative artists, these tools are amplifiers that can connect us to the natural world on a whole new level.

Kjetil Golid, a generative artist from Norway, has been developing a series of artworks inspired by one-dimensional cellular automata and noise fields. His process results in bold works with basket weave-like patterns that resemble graphic pixelated flags or banners. These works recall computing origins in the Jacquard loom, a device that employed punch cards to simplify the intricate weaving process of 18th-century textiles. Golid explains his process:

‘It's based on this traditional variant where pixels can be alive or dead on a 2D grid. I thought, ‘What if you don't change the rules, but instead, you change the visualization?’ Instead of using black and white pixels, I use lines that can go in different directions. While a 'standard' one-dimensional cellular automata gets a pixel value from its three northern neighbors, this one is a hexagonal grid with lines in three directions. The existence of a specific line is dependent on the existence of its three 'preceding' lines. The lines split up the whole area into separate spaces, and I proceed to fill these spaces with colors. The colors are selected using a one-dimensional cellular automata, with the color of each space being based on the left and upper neighboring spaces.

It turned out quite nice. It seems so random, but it is actually based on strict rules. The only seed for this randomness is the number you give it. So whenever you give it the number 120, you get exactly the same output. But it seems so random because it turns so complex so fast. The noise part comes from another piece I made, more of a tool really, that can distort any image. ‘

It’s interesting how generative artists developed their skills in both traditional art and programming. Golid started school as a design student before switching direction and earning a Bachelor of Cognitive Science degree. He continued his education, earning a Master of Computer Science degree. He developed a fascination for structures and systems, like Turing machines, regular language, and deduction systems, which were the focus of his thesis. He found himself using programming to help himself understand and visualize these systems. However, it was actually at design school where he first started learning to program using the Processing programming language.

Not all generative art is inspired by cellular automata. Artists often develop their algorithms from what they observe in the world around them. Artist Jared Tarbell produced many of our favorite generative artworks of all time, including a well-known and much-loved work called Substrate. Perhaps his best-known algorithm, Substrate, was inspired in part by the desert sun. As Tarbell explains:

‘I was sitting in a coffee shop in Sante Fe, and there was this sticker in the window that was just blasted by the sun every day. It started to separate into these cracks, and I just saw the algorithm right there. Okay, there that first crack formed and got wider, and then another crack came off of it. I wrote the algorithm right there in the coffee shop. The desert sun is pretty brutal.’

Tarbell was encouraged to make art in the home he grew up in by his mother quite a bit. However, his college studies focused on mathematics and computer science. He shared that while he viewed the world in a computational way, he wasn't afraid to express himself or try to find beauty in the computation.

Trying to understand and position ourselves within nature by understanding its algorithms and producing our own systems through the making of art can be a profoundly spiritual experience. We see Tarbell as a generative shaman unlocking new connections between us and the natural world around us -- and those connections are not always purely logical or fully explainable. One of Tarbell's recent works, Shipibo Pattern, is inspired by the patterns seen by Shipibo people, an indigenous tribe that lives in the Amazon rainforest in Peru. The Shipibo believe that there are distinctive patterns that act as healing forces (or destructive forces). As Tarbell explains:

‘During ceremony, a particular pattern is seen and heard by these people as a description of the reality of nature. I have seen it, too. The visual pattern is not what is actually witnessed, but an attempt to represent it in two dimensions. The patterns are composed of reflection, fractal self-similarity, and recursive motifs. Many of these constructions are native phenomena of computation. The Shipibo believe that the patterns are healing on emotional, physical, and spiritual levels. My personal experience with this vision leads me to believe it is an objective reality, one that can be modeled and explored.’

Tarbell humbly concludes:

‘This generative algorithm is primarily imitating the traditional artwork of the Shipibo people. My work lacks the subtle complexity and precision of the real thing.’

Emergence is evidence of a decentralized alternative to the more prevalent centralized creation myth that dictates a sole divine architect creating the world from some kind of rational blueprint. Instead, emergence and decentralization point towards an unlimited number of simpler entities following basic rules which come together to yield spectacular results. However, understanding emergence and being spiritual are not mutually exclusive. As Tarbell shares:

‘I don't know if emergence describes everything. In fact, I kind of don't believe it does. I think there still are some very spiritual, mysterious elements to the universe. But certainly, thinking about problems computationally, you can get pretty far in understanding what's actually happening.’

Some Final Thoughts

It's been a difficult few months for people all around the world. First, we had to isolate ourselves from our friends and families to help prevent the spread of the coronavirus. Then we witnessed the brutal and senseless murder of George Floyd by the very people who are supposed to protect us. Art can seem trivial in times like this but we believe this is when we need art more than ever. We chose to create this exhibition with the hope that it can play a small role in helping us better understand the healing patterns hidden in nature that unite us all.

To inquire about the artists in this exhibition please contact us at info@katevassgalerie.com.
Link to Artnome.