In this example, each generation has a population of letter strings. Fitness value is determined based on whether a character at a specified index is "correct" (string should spell 'cyberneticbiometrics'). The mutation rate is 10%. Just like in real life, mutations allow the population to increase its average fitness value over the course of many generations. The Genetic Algorithm sacrifices the best value in hopes of achieving a better value in the next generation; however, this is not guaranteed.