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Genetic Algorithm Implementation Created by Colin Gregory May 2019 Usage: python3 genetic.py nStates nIterations nMutate Where: nStates -Integer -nStates is the number of states of the population nIterations -Integer -nInterations is the number of times the algorithm will produce new children nMutate -Integer -nMutate is the upper bound of the chance to have a child mutate Examples: The following command will start with 100 different states, producing new children 100 times, and each time a child is made it has a 1/5 chance to mutate python3 genetic.py 100 100 5 The following command will start with 5000 different states, producing new children 200 times, and each time a child is made it has a 1/10 chance to mutate. python3 genetic.py 5000 200 10
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An implementation of a genetic algorithm for the 8-queens problem using python.
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