[PYTHON] Reinforcement learning 5 Try programming CartPole?

It is assumed that reinforcement learning 4 has been completed.

Let's do some simple programming.

CartPole2.py


import gym
env = gym.make('CartPole-v0')
for i in range(20):
    observation = env.reset()
    for t in range(100):
        env.render()
        action = 0
        if observation[2]>0:
            action = 1
        observation, reward, done, info = env.step(action)
        if done:
            print("Episode{} finished after {} timesteps".format(i, t+1))
            break
env.close()

CartPole.py was moving randomly. The difference from CartPole.py is that you want to change the action due to the difference in observation. It becomes feedback control.

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