OpenAI Gym

openai_gym.py

### OpenAI GYM ###
# 1. https://gym.openai.com/docs/
# 2. https://gym.openai.com/envs/#board_game

import gym

# Create an env for RL
# print(envs.registry.all())
env = gym.make('CartPole-v0')
observation = env.reset()

# All the action spaces in the environment
print(env.action_space)

# All the possible observations of the env
# ’Box’ implies the array size [1]
print(env.observation_space)

# Knowing the limits of the observation spaces [1]
print(env.observation_space.high)
print(env.observation_space.low)

# Number of episodes
for _ in range(1000):
  env.render()

  # Your agent here (this takes random actions)
  action = env.action_space.sample() 
  observation, reward, done, info = env.step(action)

  # Reward achieved by the previous actions
  print(reward)

  if done:
    observation = env.reset()

env.close()