Towards Evaluating a Procedural Content Orchestrator Gameplay Data to Differentiate User Profiles

We tested a procedural content orchestration algorithm against 15 anonymous users, against 12 different dungeons, played 119 times in total. We used questionnaires to collect data regarding player profiles, and gameplay data to analyze if could identify profiles using them only. Using PCA and clustering techniques, we were able to identify the most important attributes one may collect from gameplay data to analyze and differentiate play-styles. We also identified that the dungeon's characteristics have a heavy influence on analyzing profiles through gameplay, and a more controlled environment may be needed to identify player profiles. More data and further analysis are needed to extract player profiles from gameplay data, but preliminary results show promise.