Update the basic example documentation (#3281)

docs/Learning-Environment-Examples.md

 * Goal: Move to the most reward state.
 * Agents: The environment contains one agent.
 * Agent Reward Function:
+  * -0.01 at each step
   * +0.1 for arriving at suboptimal state.
   * +1.0 for arriving at optimal state.
 * Behavior Parameters:
   * Visual Observations: None
 * Float Properties: None
-* Benchmark Mean Reward: 0.94
+* Benchmark Mean Reward: 0.93
 
 ## [3DBall: 3D Balance Ball](https://youtu.be/dheeCO29-EI)