Increasing generality in machine learning through procedural content generation

Sebastian Risi, Julian Togelius

Abstract: This review covers the history of procedural content generation (PCG) approaches for video games, and how these approaches are now used to generate training data and environments for machine learning models. The authors then discuss how PCG may be crucial for training agents which generalise well.