I discuss a recent study of the effectiveness of genetic algorithms (a heuristic search technique based on evolutionary dynamics) in
exploring string landscapes. I show with particular examples - with relatively small search spaces - that the technique is exceedingly efficient, and is for example able to find optimal models that occur with a frequency of 1 in 10^10, after only 10^5 constructions.