“Game level blending via machine learning, the process of combining features of game levels to create unique and novel game levels using Procedural Content Generation via Machine Learning (PCGML) techniques, has gained increasing popularity in recent years. However, many existing techniques rely on human-annotated level representations, which limits game level blending to a limited number of annotated games. … In this paper, we present a novel approach to game level blending … that can serve as a level representation for unannotated games and a unified level representation across games without … human annotation.”

Find the paper and full list of authors at ArXiv.