Hierarchically Composing Level Generators for the Creation of Complex Structures
This addresses the problem of limited applicability of PCG to complex modern games for the video game industry, though it is incremental as it builds on existing PCG methods.
The paper tackles the challenge of generating complex structures in procedural content generation (PCG) for video games by introducing a compositional method that recursively composes simple low-level generators, resulting in more accurate satisfaction of designer requirements compared to a non-compositional baseline.
Procedural content generation (PCG) is a growing field, with numerous applications in the video game industry and great potential to help create better games at a fraction of the cost of manual creation. However, much of the work in PCG is focused on generating relatively straightforward levels in simple games, as it is challenging to design an optimisable objective function for complex settings. This limits the applicability of PCG to more complex and modern titles, hindering its adoption in industry. Our work aims to address this limitation by introducing a compositional level generation method that recursively composes simple low-level generators to construct large and complex creations. This approach allows for easily-optimisable objectives and the ability to design a complex structure in an interpretable way by referencing lower-level components. We empirically demonstrate that our method outperforms a non-compositional baseline by more accurately satisfying a designer's functional requirements in several tasks. Finally, we provide a qualitative showcase (in Minecraft) illustrating the large and complex, but still coherent, structures that were generated using simple base generators.