This document provides an overview of genetic algorithms including: 1. Genetic algorithms are search and optimization techniques inspired by Darwinian evolution. 2. They work by evolving a population of candidate solutions over generations to find an optimal or near-optimal solution. 3. The main genetic operators are selection, crossover, and mutation which mimic natural selection and genetics to manipulate the composition of candidate solutions in the population from one generation to the next.