openai-gym

I've just installed openAI gym on Google Colab, but when I try to run 'CartPole-v0' environment as explained here . Code: import gym env = gym.make('CartPole-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 I get this: WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. -------------------------------------------------------------

I am trying to get the code below to work. import gym env = gym.make("CartPole-v0") env.reset() env.render() I have no problems running the first 3 lines but when I run the 4th I get the error: Traceback (most recent call last): File "<ipython-input-3-a692a1a1ffe7>", line 1, in <module> env.render() File "/home/mikedoho/gym/gym/core.py", line 150, in render return self._render(mode=mode, close=close) File "/home/mikedoho/gym/gym/core.py", line 286, in _render return self.env.render(mode, close) File "/home/mikedoho/gym/gym/core.py", line 150, in render return self._render(mode=mode, close

I am running a python 2.7 script on a p2.xlarge AWS server through Jupyter (Ubuntu 14.04). I would like to be able to render my simulations. Minimal working example import gym env = gym.make('CartPole-v0') env.reset() env.render() env.render() makes (among other things) the following errors: ... HINT: make sure you have OpenGL install. On Ubuntu, you can run 'apt-get install python-opengl'. If you're running on a server, you may need a virtual frame buffer; something like this should work: 'xvfb-run -s \"-screen 0 1400x900x24\" python <your_script.py>'") ... NoSuchDisplayException: Cannot

I have created a custom environment, as per the OpenAI Gym framework; containing step , reset , action , and reward functions. I aim to run OpenAI baselines on this custom environment. But prior to this, the environment has to be registered on OpenAI gym. I would like to know how the custom environment could be registered on OpenAI gym? Also, Should I be modifying the OpenAI baseline codes to incorporate this? You do not need to modify baselines repo. Here is a minimal example. Say you have myenv.py , with all the needed functions ( step , reset , ...). The name of the class environment is