def nextGen(self):
cGen = len(self.generations) - 1
nGen = cGen + 1
scores = []
i = 0
for genome in self.generations[cGen].genomes:
scores.append((i, genome.score))
i += 1
scores = np.sort(np.array(scores,
dtype=[('index', int), ('score', int)]),
order='score')
elite = list(reversed([x[0] for x in scores[30:40]]))
self.generations[cGen].elite = elite
self.generations.append(generation.Generation(nGen))
for i in range(40):
if i < 5:
self.generations[nGen].genomes[i].cross(
self.generations[cGen].genomes[elite[i]],
self.generations[cGen].genomes[elite[i]])
else:
mum = np.random.randint(10)
dad = np.random.randint(10)
self.generations[nGen].genomes[i].cross(
self.generations[cGen].genomes[elite[mum]],
self.generations[cGen].genomes[elite[dad]])
self.generations[nGen].genomes[i].mutate()
def create_geneology(self):
# create GENERATIONS generations
for i in tqdm(range(self.parameters.GENERATIONS)):
# create an empty generation
gen = generation.Generation(i)
if i == 0:
self.populate_first_generation(gen)
else:
# fill the generation (create children from parents in previous generations)
self.populate_generation(gen)
self.add_generation(gen)
import generation
import numpy as np
X = np.array([
[0, 0],
[0, 1],
[1, 0],
[1, 1],
])
y = np.array([
[0],
[1],
[1],
[0],
])
G = generation.Generation(X, y, pop_size=4)
G.calc_fitness()
for i in range(4):
G.next_generation()
G.calc_fitness()
G.print_gen_info()
def __init__(self):
self.generations = [generation.Generation(0)]
self.generations[0].initialGeneration()
def __init__(self, root_dir):
self.root = root_dir
self.percept = perception.Perception(self.root)
self.generate = generation.Generation(self.root)
def main(self):
""" Instances generation 0, evolves the population, plots values."""
self.pop = generation.Generation(self.X, self.y, pop_size=self.size)
self.evolve()
self.print_best_net()
self.plot_results()
def main(self):
""" Instantiates generation 0, evolves the population, plots fitness values."""
self.pop = generation.Generation(self.data, self.exp, self.size)
self.evolve()
self.print_best_net()
self.plot_results()
def main():
game = Game()
snake = Snake(game)
if len(sys.argv) == 1:
print "Running in regular mode"
else:
if sys.argv[1] == "watch":
args = {}
for arg in sys.argv[2:]:
split = arg.split('=')
args[split[0]] = split[1]
if "name" not in args:
args["name"] = "."
snake.brain.ihBias = pickle.load(open("trained_model/"+args["name"]+"/ihBias.pb", "rb"))
snake.brain.hhBias = pickle.load(open("trained_model/"+args["name"]+"/hhBias.pb", "rb"))
snake.brain.hoBias = pickle.load(open("trained_model/"+args["name"]+"/hoBias.pb", "rb"))
snake.brain.ihWeights = pickle.load(open("trained_model/"+args["name"]+"/ihWeights.pb", "rb"))
snake.brain.hhWeights = pickle.load(open("trained_model/"+args["name"]+"/hhWeights.pb", "rb"))
snake.brain.hoWeights = pickle.load(open("trained_model/"+args["name"]+"/hoWeights.pb", "rb"))
pygame.init()
win = pygame.display.set_mode((720, 480))
pygame.display.set_caption("Snake Neural Network - Watching")
clock = pygame.time.Clock()
snake.brain.play(win, True)
pygame.quit()
return
elif sys.argv[1] == "train":
args = {}
for arg in sys.argv[2:]:
split = arg.split('=')
args[split[0]] = split[1]
if "name" not in args:
args["name"] = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
if "pop" not in args:
args["pop"] = 80
else:
args["pop"] = int(args["pop"])
if "gen" not in args:
args["gen"] = 1000
else:
args["gen"] = max(int(args["gen"]), 4)
if "display" not in args:
args["display"] = 0
else:
args["display"] = int(args["display"])
gen = generation.Generation(args["pop"], util.DEFAULT_INPUT_SIZE, util.DEFAULT_HIDDEN_SIZE , util.DEFAULT_OUTPUT_SIZE)
for _ in range(args["gen"]):
gen.train(args["name"], None)
gen.saveBestGenomes()
gen.mutate()
print("Training completed")
return
pygame.init()
win = pygame.display.set_mode((720, 480))
pygame.display.set_caption("Snake Neural Network - Regular")
clock = pygame.time.Clock()
while not game.over:
clock.tick(20)
movedirection = snake.direction
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.quit()
sys.exit()
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_LEFT:
movedirection = 27
elif event.key == pygame.K_RIGHT:
movedirection = 26
elif event.key == pygame.K_UP:
movedirection = 24
elif event.key == pygame.K_DOWN:
movedirection = 25
if game.board[util.positionOnceTowardsDirection(snake.cells[0], game, movedirection)] == 2:
print("Snake's score is now {}, length {}".format(game.score+100, snake.length+3))
snake.move(movedirection)
win.fill((0,0,0))
game.display(win)
pygame.display.update()
print("You ended with a score of {}".format(game.score))
pygame.quit()
sys.exit()