Curriculum docs specify that Academy must be reset.

docs/Training-Curriculum-Learning.md

 Once our curriculum is defined, we have to use the reset parameters we defined
 and modify the environment from the agent's `AgentReset()` function. See
 [WallJumpAgent.cs](https://github.com/Unity-Technologies/ml-agents/blob/master/unity-environment/Assets/ML-Agents/Examples/WallJump/Scripts/WallJumpAgent.cs)
-for an example.
+for an example. Note that if the Academy's __Max Steps__ is not set to some
+positive number the environment will never be reset. The Academy must reset
+for the environment to reset.
 
 We will save this file into our metacurriculum folder with the name of its
 corresponding Brain. For example, in the Wall Jump environment, there are two