Genetic algorithms are a family of computational search and learning methods inspired by biological evolution. Evolution takes place on a population of individuals, each of which represents a candidate solution to a given problem. At a given generation, each individual's fitness is calculated according to a user-defined fitness function. A selection process probabilistically chooses the fittest individuals to reproduce (with variation resulting from crossover and mutation); their offspring make up the next generation. The algorithm runs for either a fixed number of generations, or until an individual is found whose fitness is above a user-defined threshold.
- Evolution, Adaptation, Computer Science, Artificial Life, Artificial Intelligence