In the 1935 operatic film Naughty Marietta there is a rather lovely song titled “Ah! Sweet Mystery of Life” that opens with these lyrics:
You can find the 1935 version of the song on YouTube here. The “Sweet Mystery” it describes is the feeling of being passionately in love.
In the 1974 comedy horror classic Young Frankenstein Mel Brooks used the song as a bit of a “running gag” and the “Sweet Mystery” sometimes alluded to the secret that Dr. Frankenstein had discovered which enabled the “reanimation” of the monster, while other times Mel Brooks use the song to allude love and or sex.
Four years prior to the theatrical release of Young Frankenstein there was a young mathematician contemplating his own “sweet mystery” that lead to mysterious “creatures” not of once dead flesh and bone but rather were mathematical in nature and they seemed to have minds of their own!
In 1970 John Horton Conway or more frequently referred to as just “Conway”, was inspired by mathematician John von Neumann (are most mathematician’s named John? 😛 ) to explore the concepts of universal self-replication, evolution and simulations when he came across the Von Neumann Universal Constructor.
The Universal Constructor is a machine constructed out of 2D cellular automata that is capable of reproducing itself and also which exhibits evolutionary growth and variability in its operation.
When Von Neumann created the Universal Constructor he designed it using 29 cell states and an orthogonal neighborhood restricted to the four cardinal points.
The Von Neumann Neighborhood
The technical brilliance of the Universal Constructor cannot be overstated! However, Conway wasn’t satisfied with the engineered complexity that was required for the Universal Constructor to work and became convinced that fewer and simpler rules could be used that would allow complexity to emerge as a byproduct of the system.
- 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.
Conway experimented with various ways to simplify Von Neumann’s 29 state rule set and eventually became convinced that you could use only two states, zero and one and these are colloquially refereed to as “dead” and “alive” states.
A Mad Scientist Experiments
It was 1970 and the personal computer revolution wouldn’t even start for the better part of a decade (The Apple I was released in 1976) and what most people thought of as a computer at the time was called a “Mainframe” and a single Mainframe could easily take up an entire large room!
Like Dr. Victor Von Frankenstein who had to invent new tools and methodologies in order to bring his creation to life, Conway had to get creative to experiment with his rules!
So, Conway started his experiments using only paper and pencils but quickly graduated to using Go boards laid out on coffee tables and floors to create the 2D grid or plane on which Conway’s Game of Life is “played”.
One day, after making a few changes to his rule set he sat down with some friends and colleagues to run a new experiment and not long after they had started came an excited exclamation from across the grid “It’s walking!”… almost seeming to mirror the “It’s Alive” scene in the 1931 adaptation of Frankenstein:
While not abiogenesis (the origin of life or “life from lifelessness”) as Dr. Frankenstein had accomplished, certainly it was none the less a thrilling moment for everyone present!
Everyone crowded around the corner of the Go board to observe the discovery.
What they had witnessed was the the first “creature” brought to life in a game that would come to be called “Conway’s Game of Life“.
The creature they observed “walking” is now called a “Glider” and it looks like this:
I hope you enjoyed this post! If you liked this topic please come back tomorrow and we will dig into Conway’s rules and look into how we might use Conway’s Game of Life in our Ancestor Simulation, thank you!
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