Gym Documentation: Standard API & Reference Environments for Reinforcement Learning (original) (raw)

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Gym is a standard API for reinforcement learning, and a diverse collection of reference environments.#

Lunar Lander

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) # User-defined policy function observation, reward, done, info = env.step(action)

if done: observation, info = env.reset(return_info=True) env.close()