root `index` legacy
Game of Life Complex behavior can emerge from very simple rules. The game of live is a great example of this. Talking about how it works and how you can try it out! `2020-05-02` Try it! Intro The Game of Life is a cellular automaton that was created by the mathematician John Conway in 1970. It takes an initial state of cells, and through time steps and simple rules, it mutates the state of the cells in the grid. I had already programmed another version of the game of life in my first website, but it was slow and inefficient. Demo Here is a video of the program running on my phone, with a random starting state: video If you wish to try it for yourself, you can click here! Draw cells by clicking or dragging your mouse or start from a random state, and click Play to see the cells evolve! How it Works This, as stated in the introduction, is a cellular automaton. A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off. The grid can be in any finite number of dimensions. For each cell, a set of cells called its neighborhood is defined relative to the specified cell. An initial state is selected by assigning a state for each cell. A new generation is created (advancing time by 1), according to some fixed rule (generally, a mathematical function). Wikipedia It consists of a 2D grid of cells which can be in one of two states: alive or dead. In the program, the grid of cells is implemented by an `HTML canvas` for the best performance. By looking at the states of its neighbors (a 3x3 square around a cell), it can modify its own state according to 4 simple rules. They are the following: Any live cell with fewer than two live neighbours dies, as if by underpopulation. Any live cell with two or three live neighbours lives on to the next generation. Any live cell with more than three live neighbours dies, as if by overpopulation. Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction. Wikipedia As you have seen in the video in the Demo section, very complex behavior can emerge from these four very simple rules! Conclusion I programmed and optimized this cellular automaton in a few hours, and it wasn't too hard to make it work due to the simplicity of the rules it uses. Despite that, I had a lot of fun making it and I am really pleased with the final result!
© 2025 Emilien Breton `legacy/Game-of-Life/index.md`

Game of Life

Complex behavior can emerge from very simple rules. The game of live is a great example of this. Talking about how it works and how you can try it out! 2020-05-02

Try it!

Intro

The Game of Life is a cellular automaton that was created by the mathematician John Conway in 1970. It takes an initial state of cells, and through time steps and simple rules, it mutates the state of the cells in the grid. I had already programmed another version of the game of life in my first website, but it was slow and inefficient.

Demo

Here is a video of the program running on my phone, with a random starting state:

video

If you wish to try it for yourself, you can click here! Draw cells by clicking or dragging your mouse or start from a random state, and click Play to see the cells evolve!

How it Works

This, as stated in the introduction, is a cellular automaton.

A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off. The grid can be in any finite number of dimensions. For each cell, a set of cells called its neighborhood is defined relative to the specified cell. An initial state is selected by assigning a state for each cell. A new generation is created (advancing time by 1), according to some fixed rule (generally, a mathematical function).

Wikipedia

It consists of a 2D grid of cells which can be in one of two states: alive or dead. In the program, the grid of cells is implemented by an HTML canvas for the best performance. By looking at the states of its neighbors (a 3x3 square around a cell), it can modify its own state according to 4 simple rules. They are the following:

Any live cell with fewer than two live neighbours dies, as if by underpopulation.

Any live cell with two or three live neighbours lives on to the next generation.

Any live cell with more than three live neighbours dies, as if by overpopulation.

Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.

Wikipedia

As you have seen in the video in the Demo section, very complex behavior can emerge from these four very simple rules!

Conclusion

I programmed and optimized this cellular automaton in a few hours, and it wasn't too hard to make it work due to the simplicity of the rules it uses. Despite that, I had a lot of fun making it and I am really pleased with the final result!