Gym’s documentation#
Gym is a standard API for reinforcement learning, and a diverse collection of reference environments.
The Gym interface is simple, pythonic, and capable of representing general RL problems:
import gym
env = gym.make("LunarLander-v2")
observation, info = env.reset(seed=42, return_info=True)
for _ in range(1000):
env.render()
action = policy(observation)
observation, reward, done, info = env.step(action)
if done:
observation, info = env.reset(return_info=True)
env.close()