Great introduction for those new to GAs. I’ve been working with GAs for about 19 years now and another way that my business partner and I have represented them is as binary trees. With this concept you can think of mutation as “leaf replacement” or “branch modification”, and crossover as “branch substitution”. We’ve seen similar gains in performance by utilizing GAs for machine learning — especially in areas where the problem space is too large to explore deterministically.