Gym

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", render_mode="human") observation, info = env.reset(seed=42) for _ in range(1000): action = policy(observation) # User-defined policy function observation, reward, ter

[dirablue]

AI deep learning game TensorFlow

[yoshihiroueda]

強化学習の勉強用。

[chess-news]

　環境　モデル

[hijikiwakame]

openaigym

[kent-where-the-light-is]

“A toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Go.”

[atotto]

少し遊んでみよかな

[tuki0918]

hoge-

[nikutaiha]

強化学習

[kaz_uki_1014]

Open source interface to reinforcement learning tasks.The gym open-source project provides a simple interface to a growing collection of reinforcement learning tasks. You can use it from Python, and ...

[barlog]

toolkit

[nagayama]

なんかかわいい

[roomba]

おもしろそう！

[root]

"A toolkit for developing and comparing reinforcement learning algorithms"

[elu_18]

Announcing OpenAI Gym: a toolkit for standardizing RL environments and evaluation +blog post https://t.co/tKyp7Ftnqw https://t.co/SCQiWHFquC