This is a fork from https://github.com/wsgdrfz/gymgrid. The original implementation does no longer work in the latest versions of gym due to the change from the pyglet renderer to pygame.
The gridworld environment contains simple environments in RL book and compatible with OpenAI-gym.
pip install gymgrid2
import gym
import gymgrid2
env = gym.make('cliff-v0')
for i_episode in range(20):
observation = env.reset()
for t in range(100):
env.render()
print(observation)
action = env.action_space.sample()
observation, reward, done, info = env.step(action)
if done:
print("Episode finished after {} timesteps".format(t+1))
break
env.close()
print("env closed")
- Sample1
- Sample2
- Cliff: Example 6.5: Cliff Walking
- WindyGridWorld: Exercise 6.9 Windy Gridworld with King's Moves