Generating levels for Super Mario Bros using advanced level design concepts

Procedural content generation (PCG) is a long-used approach for creating a sizable volume of playable levels in games. Such levels often lack the quality and theme consistency of hand-crafted ones. The aim of this thesis is to explore the principles used by Nintendo in their human-made levels and to apply them to procedural generation. That could improve players' experience while preserving the benefits of PCG. We have developed an example level generator for the Super Mario game demonstrating these principles. We have also compared its output to other level generators and the original Nintendo games in known metrics. Additionally, we have conducted a study examining subjective player enjoyment. It shows that this approach increases the level enjoyment and decreases the player's frustration.