OpenAI Gym CartPole - Hand-made Policy (learn)

hand_made_policy_learn.py

env = gym.make('CartPole-v0')

for i_episode in range(200):
    observation = env.reset()
    rewards = 0
    for t in range(250):
        env.render()

        action = choose_action(observation)
        observation, reward, done, info = env.step(action)

        rewards += reward

        if done:
            print('Episode finished after {} timesteps, total rewards {}'.format(t+1, rewards))
            break

env.close()