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4 changes: 2 additions & 2 deletions docs/Installation-Windows.md
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Expand Up @@ -166,10 +166,10 @@ Make sure to replace the relevant directory location with the one you have insta
</p>

### Install TensorFlow GPU
Next, install `tensorflow-gpu` using `pip`. In an Anaconda Prompt with the Conda environment ml-agents activated, type in the following command _(make sure you are connected to the internet)_:
Next, install `tensorflow-gpu` using `pip`. You'll need version 1.4.0 as newer version require CUDA 9 which is not yet supported. In an Anaconda Prompt with the Conda environment ml-agents activated, type in the following command _(make sure you are connected to the internet)_:
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"as newer version" --> "as newer versions"


```
pip install tensorflow-gpu
pip install tensorflow-gpu==1.4.0
```

Lastly, you should test to see if everything installed properly and that TensorFlow can identify your GPU. In the same Anaconda Prompt, type in the following command:
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2 changes: 1 addition & 1 deletion docs/Learning-Environment-Examples.md
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Expand Up @@ -109,7 +109,7 @@ If you would like to contribute environments, please see our
* -0.0005 for every step.
* +1.0 if the agent touches the goal.
* -1.0 if the agent falls off the platform.
* Brains: One brain with the following observation/action space.
* Brains: Two brains, each with the following observation/action space.
* Vector Observation space: (Continuous) 16 variables corresponding to position and velocities of agent, block, and goal, plus the height of the wall.
* Vector Action space: (Discrete) Size of 74, corresponding to 14 raycasts each detecting 4 possible objects. plus the global position of the agent and whether or not the agent is grounded.
* Visual Observations: None.
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