text: import argparse
  from copos import *
  import tensorflow as tf
  import hyperparameters as h
  # import gym, gym.spaces
  # import rl_botics.env.gym_pomdp
  # from rl_botics.envs.fvrs import *
  from rl_botics.envs.table_continuous import *
  from rl_botics.envs.table_continuous_with_time import *
  from rl_botics.common.utils import save_model
  import os
  
  def argparser():
      parser = argparse.ArgumentParser()
      parser.add_argument('--env', type=str, default=h.env_name)
      parser.add_argument('--gamma', type=float, default=h.gamma)
      parser.add_argument('--pi_lr', type=float, default=h.pi_lr)
      parser.add_argument('--maxiter', type=int, default=h.maxiter)
      parser.add_argument('--render', type=bool, default=h.render)
      parser.add_argument('--batch_size', type=int, default=h.pi_batch_size)
      parser.add_argument('--cg_damping', type=float, default=h.cg_damping)
      parser.add_argument('--kl_bound', type=float, default=h.kl_bound)
      parser.add_argument('--ent_bound', type=float, default=h.ent_bound)
      parser.add_argument('--min_trans_per_iter', type=float, default=h.min_trans_per_iter)
      return parser.parse_args()
  
  def main():
      """
          Main script
          Default environment: CartPole-v0
      """
      args = argparser()
      env = ContinuousTable()
      # env = ContinuousTableWithTime()
      with tf.Session() as sess:
          agent = COPOS(args, sess, env)
          print("Training agent...\n")
          agent.train()
          agent.print_results()
  
          # Save trained policy
          dirname = "models"
          if not os.path.exists(dirname):
              os.makedirs(dirname)
          save_model(os.getcwd() + "/" + dirname + "/model.ckpt")
  
  if __name__ == '__main__':
      main()