Genetic algorithms. Genetic algorithms [ ] are iterative, stochastic search methods inspired by Darwinian evolution. Each NPM is represented by a "chromosome"-a vector of categorical variables that uniquely specifies its structure. A small initial generation (set) of property-labeled NPMs is iteratively evolved by applying genetic operations to their chromosomes: mutation, replication, selection, and recombination. At each generation, we conduct experiments on each newly evolved NPM to evaluate its fitness. This guides the genetic operations used to evolve to the next generation of chromosomes (representing NPMs), with the ambition of both exploring NPM space and enriching future generations with high-fitness NPMs. See Refs. as examples.