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Multiple copies are made of them, but the copies are not perfect; random changes are introduced during the copying process.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.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" (!), no amount of time or genetic change can transform one "kind" into another.The GA then evaluates each candidate according to the fitness function.In a pool of randomly generated candidates, of course, most will not work at all, and these will be deleted.A third approach is to represent individuals in a GA as strings of letters, where each letter again stands for a specific aspect of the solution.

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 .

The expectation is that the average fitness of the population will increase each round, and so by repeating this process for hundreds or thousands of rounds, very good solutions to the problem can be discovered.

As astonishing and counterintuitive as it may seem to some, genetic algorithms have proven to be an enormously powerful and successful problem-solving strategy, dramatically demonstrating the power of evolutionary principles.

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

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