Application of machine learning to monster level prediction in tabletop RPG game design
The episode discusses a paper applying machine learning to predict monster levels in TTRPGs using a large dataset of Pathfinder entries. The authors framed the task as 'tabular ordinal regression' and found that tree-based ensembles perform exceptionally well. The conclusion suggests AI can provide practical, data-driven assistance for balancing game worlds.