Genetic Algorithms: From Line Fitting to the...

Imagine you're planning a road trip through 25 cities. The number of possible routes is 25!/2 — roughly 7.8 × 10²⁴, more than the number of stars in the observable universe. You can't try them all. And unlike fitting a line with gradient descent, there's no gradient to follow — the search space is discrete and rugged. Nature solved this class of problem billions of years ago. Evolution doesn't need gradients. It works through variation and selection: generate diverse candidates, keep the ones th