from comps.eng_norm.run import run_sol
elif FLAGS.comp == "russian_norm":
from comps.russian_norm.run import run_sol
elif FLAGS.comp == "caesars":
from comps.caesars.run import run_sol
elif FLAGS.comp == "personal":
from comps.personal.run import run_sol
else:
print("Unknown competion %s" % FLAGS.comp)
assert False
print("run competition %s solution %s" % (FLAGS.comp, FLAGS.sol))
run_sol(FLAGS)
if __name__ == "__main__":
try:
import tensorflow as tf
use_flags = "tf"
except:
use_flags = "arg"
if use_flags == "tf":
from tf_flags import FLAGS
tf.app.run()
else:
from flags import get_parser
parser = get_parser()
args = parser.parse_args()
FLAGS = args
main(None)
min_unit = None
enemy_id = 0
for i in range(5, len(obs), 5):
x = obs[i]
y = obs[i + 1]
if min_value > x * x + y * y:
min_value = x * x + y * y
min_unit = enemy_id
enemy_id += 1
return self.move_actions + min_unit
if __name__ == '__main__':
args = get_parser().parse_args()
args.unlimited_attack_range = True
args.unlimited_vision = True
env = StarCraftMvN(args, final_init=True)
agent = AttackClosestAgent(env.action_space)
agent.set_move_steps(len(env.move_steps))
episodes = 0
success = 0
while episodes < 500:
obs = env.reset()
done = False
total_reward = 0
while not done: