OpenAI Gym CartPole - Random Action

random_action.py

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

# 跑 200 個 episode，每個 episode 都是一次任務嘗試
for i_episode in range(200):
    observation = env.reset() # 讓 environment 重回初始狀態 
    rewards = 0 # 累計各 episode 的 reward 
    for t in range(250): # 設個時限，每個 episode 最多跑 250 個 action
        env.render() # 呈現 environment

        # Key section
        action = env.action_space.sample() # 在 environment 提供的 action 中隨機挑選
        observation, reward, done, info = env.step(action) # 進行 action，environment 返回該 action 的 reward 及前進下個 state

        rewards += reward # 累計 reward

        if done: # 任務結束返回 done = True
            print('Episode finished after {} timesteps, total rewards {}'.format(t+1, rewards))
            break

env.close()