Cellular automaton where cells live, die, or reproduce based on simple rules.
Conway's Game of Life is a zero-player cellular automaton devised by mathematician John Horton Conway in 1970. Despite having no input after the initial state, astonishingly complex patterns emerge from just four simple rules applied to a grid of cells. It is one of the most famous examples of emergent behavior -- how complex systems arise from simple rules -- and has deep connections to computability theory, as it has been proven to be Turing complete.
| Current State | Live Neighbors | Next State |
|---|---|---|
| Alive | < 2 | Dead (underpopulation) |
| Alive | 2 or 3 | Alive (survival) |
| Alive | > 3 | Dead (overpopulation) |
| Dead | exactly 3 | Alive (reproduction) |
These four rules are applied to every cell simultaneously. The key insight is that all births and deaths happen at the same instant -- no cell's new state affects another cell's computation in the same generation.
| Metric | Value |
|---|---|
| Time per generation | O(N × M) |
| Space | O(N × M) |
Where N × M is the grid size. Each cell requires checking its eight neighbors, making each generation linear in the number of cells. Advanced implementations like HashLife can achieve exponential speedups for patterns with repeated structure by memoizing sub-patterns.
The Game of Life has applications across many fields. In theoretical computer science, it demonstrates that simple rules can produce universal computation -- logic gates, memory, and even entire computers have been built within it. In biology, it models population dynamics, bacterial colony growth, and pattern formation in organisms. In physics, it serves as a simplified model for studying phase transitions and self-organization. It remains a cornerstone of recreational mathematics and a gateway to understanding cellular automata, complexity theory, and artificial life.