text: import ROOT
  import gym
  import pandas as pd
  
  env = gym.make('CartPole-v1')
  env.reset()
  
  agent = ROOT.HTMAgent()
  et = ROOT.et
  
  reward_history = []
  learn = True
  for n in range(5000):
          observation = env.reset()
          total_reward = 0
          for i in range(1000):
                  # env.render() # Somehow this doesn't work on my system
  
                  v0 = observation[0]
                  v1 = observation[1]
                  v2 = observation[2]
                  v3 = observation[3]
  
                  action = agent.compute(v0, v1, v2, v3, learn)
                  observation, reward, done, info = env.step(action)
                  if learn:
                      agent.learn(-1 if done else reward)
  
                  if done:
                          break
                  total_reward += reward
          agent.reset()
          print("Iteration {}, reward = {}".format(n, total_reward))
          reward_history += [total_reward]
  
  df = pd.DataFrame({"reward": reward_history})
  savefile = "result_{}learning.csv".format("no_" if learn is False else "")
  df.to_csv(savefile)
  