A GPU simulation of Conway’s Game of Life – a basic cellular automation. Each cell in the scene holds one of two states – dead (black) or alive (white). The destiny of each these tiny imaginary beings is determined by the eight neighbouring cells that surround it. The following four rules define the evolution of the ‘game’:
1. Living cells with fewer than two neighbours die. (Under-population)
2. Living cells with either two or three neighbours carry on doing their thing.
3. Living cells with greater than three neighbours die. (Over-population)
4. Dead cells with exactly three neighbours come to life. (Reproduction)
The astonishing thing about Conway’s Game of Life is the depth of intricacy that emerges from a simple set of elementary and deterministic laws. Simulations such as this should humble our understanding of the unimaginable complexities of the living world.
It’s also worth noting that this simulatuion has the computational power of a universal Turing machine – i.e, anything that is algorithmically computable can be theoretically computed within the Game of Life. This has been extensively explored, some even gone so far as to compute the Game of Life within a Game of Life simulation – creating a sort of fractal-meta-simulation:
Youtube Credit: Phillip Bradbury