Cold fix to develop : documentation for Engine Configuration (#3028)

* Cold fix to develop : documentation for Engine Configuration

* added --time-scale to getting started guide

* Trailing white space

docs/Getting-Started-with-Balance-Ball.md

 
 ### Academy
 
-The Academy object for the scene is placed on the Ball3DAcademy GameObject. When
-you look at an Academy component in the inspector, you can see several
-properties that control how the environment works.
-The **Training Configuration** and **Inference Configuration** properties
-set the graphics and timescale properties for the Unity application.
-The Academy uses the **Training Configuration**  during training and the
-**Inference Configuration** when not training. (*Inference* means that the
-Agent is using a trained model or heuristics or direct control — in other
-words, whenever **not** training.)
-Typically, you would set a low graphics quality and timescale to greater `1.0` for the **Training
-Configuration** and a high graphics quality and timescale to `1.0` for the
-**Inference Configuration** .
-
-**Note:** if you want to observe the environment during training, you can adjust
-the **Training Configuration** settings to use a larger window and a timescale
-closer to 1:1. Be sure to set these parameters back when training in earnest;
-otherwise, training can take a very long time.
-
-Another aspect of an environment is the Academy implementation. Since
+The Academy object for the scene is placed on the Ball3DAcademy GameObject. Since
 the base Academy class is abstract, you must always define a subclass. There are
 three functions you can implement, though they are all optional:
 
 To summarize, go to your command line, enter the `ml-agents` directory and type:
 
 ```sh
-mlagents-learn config/trainer_config.yaml --run-id=<run-identifier> --train
+mlagents-learn config/trainer_config.yaml --run-id=<run-identifier> --train --time-scale=100
 ```
 
 When the message _"Start training by pressing the Play button in the Unity
 environment first.
 
 The `--train` flag tells the ML-Agents toolkit to run in training mode.
+The `--time-scale=100` sets the `Time.TimeScale` value in Unity.
 
 **Note**: You can train using an executable rather than the Editor. To do so,
 follow the instructions in

docs/Learning-Environment-Design.md

 efficient and practical to create a purpose-built training scene.
 
 Both training and testing (or normal game) scenes must contain an Academy object
-to control the agent decision making process. The Academy defines several
-properties that can be set differently for a training scene versus a regular
-scene. The Academy's **Configuration** properties control rendering and time
-scale. You can set the **Training Configuration** to minimize the time Unity
-spends rendering graphics in order to speed up training.
+to control the agent decision making process.
 When you create a training environment in Unity, you must set up the scene so
 that it can be controlled by the external training process. Considerations
 include: