Where am I? - On Providing Gamebots with a Sense of Location Using Spectral Clustering of Waypoints

Most computer games that are set in simulated 3D worlds require the player to act according to his or her current location. For the programming of convincing artificial game agents this poses the problem of providing them with a sense of where they are. However, due to the growing size and complexity of games, manual annotations that capture all essential areas and aspects may soon become infeasible. In this paper, we therefore propose a data-driven approach to the semantic clustering of in-game locations. Following the paradigm of gamebot programming by human demonstration, we apply the technique of spectral clus- tering to automatically derived waypoint maps. First results underline that this approach indeed provides spatial partitions of game maps that make sense from a gamers point of view.