Skip to Main Content
In this paper we propose a method of video game player modeling based on clustering of behavior data collected during game play. Based on the style of play, and game mechanics, we define two player types the action player and the tactical player. We then use the CURE clustering method to classify the game players according to their style of play. We demonstrate that the CURE algorithm can successfully assign the per-defined gamer type. The knowledge of the gamer type can then be used to adjust the game difficulty accordingly.