ABSTRACT
The genetic algorithm models the genetic process that gives rise to evolution. In particular, it models sexual reproduction, where both parents give some genetic information to their offspring. The Genetic Algorithm is a computational approximation to how evolution performs search, which is by producing modifications of the parent genomes in their offspring and thus producing new individuals with different fitness. The fitness function can be seen as an oracle that takes a string as an argument and returns a value for that string. One extension of genetic algorithms that has had a lot of attention is the idea of genetic programming. The power of these developments of the Genetic Algorithm (GA) is that they use probabilistic models and are therefore more amenable to analysis than normal GAs, which have steadfastly withstood many attempts to better understand their behaviour.
