Java Deep Learning Cookbook

How it works...

In step 1, we added RL4J core dependencies to bring in RL4J DQN libraries in our application. RL4J Malmo dependencies are added in step 2 to construct the Malmo environment and build missions in RL4J.

We need to add CPU/GPU-specific ND4J backend dependencies as well (step 3). Finally, in step 4, we added dependencies for MalmoJavaJar (step 4), which acts as a communication interface for the Java program to interact with Malmo.