Authors: Jonas P Knochelmann
Mentors: Rogelio E. Cardona-Rivera
Insitution: University of Utah
Despite the highly technical nature of Procedural Content Generation (PCG), the holistic study of the discipline is minimal and qualitative. We argue that this gap exists because there is no formal framework to talk about PCG artifacts and algorithms and propose the mathematical field of group theory to serve as such a framework. Group theory is a well-established discipline that has been embraced in chemistry, physics, and art, with tools for analyzing, combining, and generating objects based on their structure. We outline a specific method for applying group theory to PCG and explore a number of case studies in the hopes of developing a more unified formal framework for future study.