Genetic-Algorithm

The genetic algorithm is comprised of 6 central features:
  1. A randomized initial population (size 100)
  2. A fitness function, which both prescribes a fitness score to each individual in the the population and orders the fitness scores in preparation for culling
  3. The culling selection mechanism that eliminates the bottom half of individuals in the
population (culling_rate = .5)
  4. A reproduction function to re-populate after each gen's culling
  5. Mutation (mutation_rate = .01)
  6. An Iterator, with a break point to end each generation (convergence = 200)

To set up the environment, a box class was created to instantiate the 12 input boxes. The algorithm is looped over 10 times to represent 10 different generations. The four toggles for this algorithm -- mutation_rate, convergence, generation number, and initial population -- can all be found in the for loop at the bottom of python file.