def runGA():
myWorld = World([
[0, 0, 0, 0, 1, 0, 1, 3, 1],
[1, 0, 1, 1, 1, 0, 2, 3, 1],
[1, 0, 0, 1, 3, 3, 3, 3, 1],
[3, 3, 3, 1, 3, 1, 1, 0, 1],
[3, 1, 3, 3, 3, 1, 1, 0, 0],
[3, 3, 1, 1, 1, 1, 0, 1, 1],
[1, 3, 0, 1, 3, 3, 3, 3, 3],
[0, 3, 1, 1, 3, 1, 0, 1, 3],
[1, 3, 3, 3, 3, 1, 1, 1, 4],
])
ga = GA(20, 0.05, 0.9, 2, 10)
population = ga.initPopulation(128)
ga.evalPopulation(population, myWorld)
# Keep track of current generation
generation = 1
while ga.isTerminationConditionMet(generation, maxGenerations) == False:
# Print fittest individual from population
fittest = population.getFittest(0)
print("G" + str(generation) + " Best solution (" +
str(fittest.getFitness()) + "): " + fittest.toString())
# Apply crossover
population = ga.crossoverPopulation(population)
# Apply mutation
population = ga.mutatePopulation(population)
# Evaluate population
ga.evalPopulation(population, myWorld)
# Increment the current generation
generation += 1
print("Stopped after " + str(maxGenerations) + " generations.")
fittest = population.getFittest(0)
print("Best solution (" + str(fittest.getFitness()) + "): " +
fittest.toString())
