How many units should there be in each generation of a genetic algorithm?

Question

I am working on a roguelike and am using a GA to generate levels. My question is, how many levels should be in each generation of my GA? And, how many generations should it have? It it better to have a few levels in each generation, with many generations, or the other way around?

Answer 1

There really isn't a hard and fast rule for this type of thing - most experiments like to use at least 200 members in a population at the barest minimum, scaling up to millions or more. The number of generations is usually in the 100 to 10,000 range. In general, to answer your final question, it's better to have lots of members in the population so that "late-bloomer" genes stay in a population long enough to mature, and then use a smaller number of generations.

But really, these aren't the important thing. The most critical part of any GA is the fitness function. If you don't have a decent fitness function that accurately evaluates what you consider to be a "good" level or a "bad" level, you're not going to end up with interesting results no matter how many generations you use, or how big your population is :)

Answer 2

Just as Mike said, you need to try different numbers. If you have a large population, you need to make sure to have a good selection function. With a large population, it is very easy to cause the GA to converge to a "not so good" answer early on.