Relational programming models work well for problems where a single input configuration has multiple valid solutions. Procedural Content Generation (PCG) is a class of such problems, typically in the context of virtual worlds or digital games in which interactors engage repeatedly with a virtual environment and expect to encounter variations that feel different, yet satisfy constraints related to playability and in-world consistency. For example, PCG algorithms may generate world maps, terrain, puzzle game levels, or text in dialogue or descriptions. In this talk, I will define several important properties for PCG algorithms, discuss relational programming techniques that support PCG, and motivate directions for future research in this area.

Ph.D. Carnegie Mellon University, 2015

Postdoc UC Santa Cruz, 2015-2016

Assistant Professor, NC State University, 2016-present