def main(args):
rng = Random(args.seed)
network_parameters = (105, 103, 100)
trainer = Trainer(
battleship_fitness,
args.class_size,
network_parameters,
args.cream,
rng,
args.threads
)
if args.class_location:
_, _, files = next(os.walk(args.class_location))
networks = [os.path.join(args.class_location, f)
for f in files if f.endswith(".network")]
trainer.stable = [Network.load_from_file(f) for f in networks]
else:
trainer.spawn_class()
for n in range(args.rounds):
print "Beginning round", n
trainer.run_round(battleship_trainer)
if args.output_location:
generation_dir = os.path.join(
args.output_location,
"gen_{}".format(max(n.generation for n in trainer.stable))
)
os.makedirs(generation_dir)
for network in trainer.stable:
network.save_to_file(path=generation_dir)
network, score = trainer.best
network.save_to_file(filename="best_gen{}_{}.network".format(
network.generation, score), path=args.output_location)
turns += 1
print network.name, "took", turns, "turns"
def battleship_trainer(network):
games = 5
print "Training", network.name, "for", games, "rounds"
score = sum(map(lambda n: len(list(play_battleships(n))), [network] * games)) / games
print network.name, "scored an average of", score
return score
def battleship_fitness(score):
return -score
if __name__ == "__main__":
parameters = (105, 103, 100)
print "Creating trainer"
trainer = Trainer(lambda n: -n, 20, parameters, 3)
print "Creating training function"
print "Starting training"
trainer.train(battleship_trainer, 5)
best, score = trainer.best
print "Winning network won in an average of", score, "turns"
for move in play_battleships(best):
print move
print ""
