Feature/docs visual obs (#456)

* [Documentation] Added description on how to add visual observations

* [Documentation] Forgot a paragraph

* [Documentation] Addressed comments

* [Documentation] Addressed comments, again

docs/Learning-Environment-Design-Agents.md

   
  For angles that can be outside the range [0,360], you can either reduce the angle, or, if the number of turns is significant, increase the maximum value used in your normalization formula.
  
-### Visual Observations
+### Multiple Visual Observations
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+To add a visual observation to an agent, click on the `Add Camera` button in the Agent inspector. Then drag the camera you want to add to the `Camera` field. You can have more than one camera attached to an agent.
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+![Agent Camera](images/visual-observation.png) 
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+In addition, make sure that the Agent's Brain expects a visual observation. In the Brain inspector, under `Brain Parameters` -> `Visual Observations`, specify the number of Cameras the agent is using for its visual observations. For each visual observation, set the width and height of the image (in pixels) and whether or not the observation is color or grayscale (when `Black And White` is checked).
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 ### Discrete Vector Observation Space: Table Lookup
 
 You can use the discrete vector observation space when an agent only has a limited number of possible states and those states can be enumerated by a single number. For instance, the [Basic example environment](Learning-Environment-Examples.md) in the ML Agent SDK defines an agent with a discrete vector observation space. The states of this agent are the integer steps between two linear goals. In the Basic example, the agent learns to move to the goal that provides the greatest reward.