Java Deep Learning Cookbook

How it works...

In step 1, we defined an action space for the agent by specifying a defined set of Malmo actions. For example, movenorth 1 means moving the agent one block north. We passed in a list of strings to MalmoActionSpaceDiscrete indicating an agent's actions on Malmo space.

In step 2, we created an observation space from the bitmap size (mentioned by xSize and ySize) of input images(from the Malmo space). Also, we assumed three color channels (R, G, B). The agent needs to know about observation space before they run. We used MalmoObservationSpacePixels because we target observation from pixels.

In step 3, we have created a Malmo consistency policy using MalmoDescretePositionPolicy to ensure that the upcoming observation is in a consistent ...