Answers for "openai gym tutorial"

openai gym random action

# load gym envirolment
import gym
env = gym.make('CartPole-v0')

env.reset()
for _ in range(300):
    env.render()
    env.step(env.action_space.sample()) # take a random action
env.close()

open ai gym

import gym
env = gym.make("CartPole-v1")
observation = env.reset()
for _ in range(1000):
  env.render()
  action = env.action_space.sample() # your agent here (this takes random actions)
  observation, reward, done, info = env.step(action)

  if done:
    observation = env.reset()
env.close()