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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.
To continue, please navigate to the appropriate area of the website using the four buttons above; project info refers to the scientific process of the project, program leads to the program created for this project, acknowledgements refer to the references given, and team info leads to information about us.