def main():
print("Severus start")
print("Randomizing population")
population = mgenetics.randomizePopulation()
print("Starting evolution")
for g in range(mgenetics.MaxGeneration):
generation = g + 1
print("")
print("Generation: ", generation, " - population size: ", len(population))
motherChromosome, fatherChromosome = mgenetics.selection(population)
print("Training mother")
motherDNN = mlearner.generateDNN(motherChromosome)
if fatherChromosome is not None:
print("Training father")
fatherDNN = mlearner.generateDNN(fatherChromosome)
child = mgenetics.crossover(motherDNN, fatherDNN)
else:
child = motherDNN
if generation < mgenetics.MaxGeneration-1:
population = mgenetics.breed(child, generation)
finalIndividual = child
print()
input("Press ENTER to start Final-Individual's game...")
game = mgame.Game()
result = game.playOneMatch_Predict(finalIndividual, True)
print("Score = ", result[2])
print()
print("Severus end")
#Main game loop
while not game_over(player):
# enemy.update_state(p1.fly_me(turtle))
player.update_state(p1.fly_ai(flight_params(player, enemy, game)))
#enemy.update_state(p2.fly_ai(flight_params(enemy,player,game))) # using saved for enemy
game.update_score(player, enemy)
player.move()
enemy.move()
# # To show playable animation
#game.show_status(player,enemy)
# To show quick animation
if counter % 15 == 0:
turtle.update()
scores[specie] = game.score
print("Final Score: " + str("%9.2f" % game.score) + " [GEN] " +
str(generation) + " [#] " + str(specie))
turtle.reset()
player.reset()
enemy.reset()
counter += 1
#import code; code.interact(local=dict(globals(), **locals()))
selected_dnas = gen.select_dna(SURVIVORS, DNA_SIZE, dnas, scores)
dyn_mut = MUTATION #gen.dyn_mutation(MUTATION,scores)
actual_best = dnas[np.argmax(scores)]
dnas = gen.breed(selected_dnas, SURVIVORS, SPECIES, dyn_mut, DNA_SIZE)
a = dnas
np.savetxt('save.txt', a, fmt='%f')
print("Saved: " + str(dnas))