Finding f(x) with Genetic Algorithms
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Project Info Program Acknowledgements Team Info


       This Virtual Science Fair project website is about function approximation through the use of genetic algorithms. A genetic algorithm is a computer search technique involving concepts from evolutionary biology. In it, random solutions are initially generated to represent individuals in a kind of virtual population. Each solution (individual) is given a fitness rating based on how well they solve the problem. Then, through a selection of these solutions—perhaps a certain number of them with the highest fitness—these solutions undergo reproduction. Crossovers of the surviving solutions (as well as mutation) are used to for the next generation of solutions. Thus every generation is an evolution towards the final solution, whatever the genetic algorithm is built to find.

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