Answers.Body: <p>Founded Documentation on Mapping Annotation: Mapping of RAM indexes to semantic state variables from mila-iqia</p>
  <p><a href="https://github.com/mila-iqia/atari-representation-learning/blob/master/atariari/benchmark/ram_annotations.py" rel="nofollow noreferrer">https://github.com/mila-iqia/atari-representation-learning/blob/master/atariari/benchmark/ram_annotations.py</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-03-19T18:58:05.293Z
Answers.LastActivityDate: 2022-03-19T18:58:05.293Z
Answers.UserDisplayName: Jirawat Zhou
Body: <p>I haven't been able to understand the output that OpenAI gym return for observation from this snippet</p>
  <pre><code>env = gym.make('ALE/Breakout-ram-v5', render_mode='human', obs_type='grayscale')
  obv = env.reset()
  print(obv)
  </code></pre>
  <p><a href="https://i.sstatic.net/QfAan.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/QfAan.png" alt="enter image description here" /></a></p>
  <p>from the OpenAI documentation it suggest it return the pixel data from camera, I am guessing that it a the game state representation at a given step. (I might be wrong here, I am still new to OpenAI)</p>
  <p>Assuming if it is the pixel data from camera, How can I retrieve information like where the paddle position, the ball velocity (incl. direction) such that it satisfy Markov Properties for Q-Learning</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-03-19T21:06:51.480Z
Comments.Text: Your question is off-topic here. Asking about software is off-topic here. See our on-topic page: https://ai.stackexchange.com/help/on-topic.
Comments.UserDisplayName: nbro
Tags: <reinforcement-learning><q-learning><open-ai><gym>
Title: what does the OpenAI ALE/Breakout-RAM-V5 observation return
UserDisplayName: Jirawat Zhou
ThreadText: # what does the OpenAI ALE/Breakout-RAM-V5 observation return
  
  (Asked by: username_0 on 2022-03-15)
  
  I haven't been able to understand the output that OpenAI gym return for observation from this snippet
  
  ```
  env = gym.make('ALE/Breakout-ram-v5', render_mode='human', obs_type='grayscale')
  obv = env.reset()
  print(obv)
  
  ```
  
  [![enter image description here](https://i.sstatic.net/QfAan.png)](https://i.sstatic.net/QfAan.png)
  
  from the OpenAI documentation it suggest it return the pixel data from camera, I am guessing that it a the game state representation at a given step. (I might be wrong here, I am still new to OpenAI)
  
  Assuming if it is the pixel data from camera, How can I retrieve information like where the paddle position, the ball velocity (incl. direction) such that it satisfy Markov Properties for Q-Learning
  
  **Tags:** reinforcement-learning, q-learning, open-ai, gym
  
  > **Comments:**
  > **username_1**: Your question is off-topic here. Asking about software is off-topic here. See our on-topic page: https://ai.stackexchange.com/help/on-topic.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_0 on 2022-03-19. Score: 0 | Accepted answer
  
  Founded Documentation on Mapping Annotation: Mapping of RAM indexes to semantic state variables from mila-iqia
  
  <https://github.com/mila-iqia/atari-representation-learning/blob/master/atariari/benchmark/ram_annotations.py>
  
  
  ---
  
  