The easiest way to think about procedural generation is by imagining a huge grid of square cells, where each cell has a chance to become black or white. A set of simple rules are put in place to set the scene: If a white cell has less than two black cells neighbouring it, it becomes a black cell. If a white cell has two or three white cell neighbours, it stays unchanged. If a white cell has more than three white celled neighbours, it becomes a black cell. If a black cell has exactly three white celled neighbours, it becomes a white cell too.
These simple rules can lead to strange outcomes. From infinite loops, to geometric shapes, to two-dimensional cave systems in video games, each mimicking the equally simple behavior of cellular automata. Like cellular automata, through procedural generation things are built not authorially by hand but by algorithm. The results are often random, and can be infinite and varied.
So if you're building levels of meandering caverns or creating vast landscapes or a digital topology, then it makes sense to generate endless variations of matter. But it's a lot harder when you're dealing with a concept like personality. Because, what are the parts of a person that can be made into procedural traits? In other words, how do you turn a person into an algorithm?
