openAI Gym

OpenAI Gym

OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This is the gym open-source library, which gives you access to a standardized set of environments.

https://gym.openai.com/

See What’s New section below

gym makes no assumptions about the structure of your agent, and is compatible with any numerical computation library, such as TensorFlow or Theano. You can use it from Python code, and soon from other languages.

If you’re not sure where to start, we recommend beginning with the docs on our site. See also the FAQ.

A whitepaper for OpenAI Gym is available at http://arxiv.org/abs/1606.01540, and here’s a BibTeX entry that you can use to cite it in a publication:

@misc{1606.01540, Author = {Greg Brockman and Vicki Cheung and Ludwig Pettersson and Jonas Schneider and John Schulman and Jie Tang and Wojciech Zaremba}, Title = {OpenAI Gym}, Year = {2016}, Eprint = {arXiv:1606.01540}, }

OpenAI Basics

There are two basic concepts in reinforcement learning: the environment (namely, the outside world) and the agent (namely, the algorithm you are writing). The agent sends actions to the environment, and the environment replies with observations and rewards (that is, a score).

The core gym interface is Env, which is the unified environment interface. There is no interface for agents; that part is left to you. The following are the Env methods you should know:

  • reset(self): Reset the environment’s state. Returns observation.
  • step(self, action): Step the environment by one timestep. Returns observation, reward, done, info.
  • render(self, mode=’human’, close=False): Render one frame of the environment. The default mode will do something human friendly, such as pop up a window. Passing the close flag signals the renderer to close any such windows.

open AI Gym Github repo:

https://github.com/openai/gym

karpathy’s algorithm solved on open AI Gym CartPole-v0 in 211 episodes.

Impressive!

https://scoreboard-site-1764008611.us-west-2.elb.amazonaws.com/evaluations/eval_lEi8I8v2QLqEgzBxcvRIaA