Imanol Perez

Update README.md

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Genetic algorithms simulate the evolution of a species. It starts with a random population of organisms, which represent algorithms. Then, after many generations the strongest algorithms survive. In general, genetic algorithms possess the following structure:
1. Generate a random population of organisms
1. Generate a random population of organisms.
2. Select the top performers, acording to a certain criteria (a fitness function is usually required here).
3. Perform a crossover of the outperformers to produce new children.
4. Apply a random mutation to some of the children. This way, we end up with a new generation of organisms.
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