text: import random
  import time
  import pickle
  
  import numpy as np
  
  import balance_bot_ne
  
  def main():
      policy_data = pickle.load(open("best.pkl", "rb"))
      policy = balance_bot_ne.NeuralNet.with_dictionary(policy_data)
  
      env = balance_bot_ne.BalancebotEnvUneven(vdrange=(-1.0, 1.0), render=True)
  
      while True:
          obs = env.reset()
          done = False
          total_reward = 0
  
          while not done:
              start = time.time()
              obs, reward, done = env.step(policy.forward(obs)[0])
              total_reward += reward
              diff = time.time() - start
              if diff > 0:
                  time.sleep(diff)
  
  if __name__ == "__main__":
      main()