Methods of representation Before a genetic algorithm can be put to work on any problem, a method is needed to encode potential solutions to that problem in a form that a computer can process.

These candidates may be solutions already known to work, with the aim of the GA being to improve them, but more often they are generated at random.

The GA then evaluates each candidate according to the fitness function.

These promising candidates are kept and allowed to reproduce.

Multiple copies are made of them, but the copies are not perfect; random changes are introduced during the copying process.

For example, creationists often explain the development of resistance to antibiotic agents in bacteria, or the changes wrought in domesticated animals by artificial selection, by presuming that God decided to create organisms in fixed groups, called "kinds" or .

Though natural microevolution or human-guided artificial selection can bring about different varieties within the originally created "dog-kind," or "cow-kind," or "bacteria-kind" (!

reationists occasionally charge that evolution is useless as a scientific theory because it produces no practical benefits and has no relevance to daily life.

However, the evidence of biology alone shows that this claim is untrue.

These digital offspring then go on to the next generation, forming a new pool of candidate solutions, and are subjected to a second round of fitness evaluation.