Setting up the Academy

An Academy object and component represents the training environment where we define the training configuration for our agents. You can think of an Academy as the school or classroom in which our agents will be trained. Open up the Unity editor and select the Academy object in the Hierarchy window. Then, follow these steps to configure the Academy component:

1. Set the properties for the Academy component, as shown in the following screenshot:

2. The following is a quick summary of the initial Academy properties we will cover:
   • Max Steps: This limits the number of actions your Academy will let each Agent execute before resetting itself. In our current example, we can leave this at 0, because we are only doing a single step. By setting it to zero, our agent will continue forever until Done is called.
   • Training Configuration: In any ML problem, we often break the problem into a training and test set.  This allows us to build an ML or agent model on a training environment or dataset. Then, we can take the trained ML and exercise it on a real dataset using inference.  The Training configuration section is where we will configure the environment for training.
   • Infrerence Configuration: Inference is where we infer or exercise our model against a previously unseen environment or dataset. This configuration area is where we set parameters when our ML is running in this type of environment.

The Academy setup is quite straightforward for this simple example. We will get to the more complex options in later chapters, but do feel free to expand the options and look at the properties.