def main(n,
generations_num,
load_and_play,
model_filename,
elite_size,
debug_mode=False):
if load_and_play == 0:
run_generations(n, generations_num, model_filename, elite_size)
else:
parent = SnakeNetwork()
parent.model = load_saved_model(model_filename)
game = SnakeGame(gui=True)
x = game.start()
prev_score = score = 0
prev_j = 0
x_array = []
x1_array = []
end = 0
for j in range(400):
[x, score, end] = game.step(parent.predict_action(x))
if score > prev_score:
prev_score = score
prev_j = j
if end > 0 or j - 100 > prev_j:
break
if debug_mode:
x_array.append(x)
x1_array.append(parent.model.predict(x))
if end == 0: game.end_game()
if debug_mode:
print(x_array)
print(x1_array)
def visualise(self):
game = SnakeGame(gui=True)
game.start()
for _ in range(self.goal_steps):
game_action = self.get_game_action(game)
done, score, snake, food = game.step(game_action)
if done:
break
game.end_game()
print('-----')
print('snake: ' + str(snake))
print('food: ' + str(food))
print('score: ' + str(score))
def visualise_game(self, model):
game = SnakeGame(gui=True)
_, score, snake, food = game.start()
prev_observation = self.generate_observation(snake, food)
for _ in range(self.max_steps):
predictions = []
for action in range(-1, 2):
predictions.append(
model.predict(
self.add_action_to_observation(
action, prev_observation).reshape(-1, 5, 1)))
action = np.argmax(np.array(predictions))
game_action = self.get_game_action(snake, action - 1)
done, score, snake, food = game.step(game_action)
if done:
break
else:
prev_observation = self.generate_observation(snake, food)
game.end_game()
print('snake: ' + str(snake))
print('food: ' + str(food))
print('prev_obs: ' + str(prev_observation))
print('score: ' + str(score))
def play_game(z, n, snakes_population):
fitness_array = np.zeros(n)
best_score = 0
for i, snake in enumerate(snakes_population):
game = SnakeGame()
x = game.start()
prev_score = score = steps = 0
prev_j = 0
for j in range((score + 1) * 100):
[x, score, end] = game.step(snake.predict_action(x))
if score > prev_score:
prev_score = score
prev_j = j
steps = 0
steps += 1
if end > 0 or j - (score + 1) * 50 > prev_j:
if end == 0: game.end_game()
break
if score > best_score:
best_score = score
fitness_array[i] = calculate_fitness(score, steps)
snake.set_fitness(fitness_array[i])
# print_progress("Snake game", i, len(snakes_population), start)
return [fitness_array, best_score]
