Procedural Content Generation (PCG) is a technique to generate complex and diverse environments in an automated way.

Aligning the world model with the environment for the agent's specific task is

In this work we study the problem of actively learning binary classifiers from a given concept class, i.e., learning by utilizing unlabeled data and submitting targeted queries about their labels to a domain expert. We evaluate the quality of our solutions by considering the learning curves they induce, i.e., the rate of