Sebastian Risi, Joel Lehman, David B. D'Ambrosio, and Kenneth O. Stanley (2014)
Automatically Categorizing Procedurally Generated Content for Collecting Games
In: Proceedings of the Workshop on Procedural Content Generation in Games (PCG) at the 9th International Conference on the Foundations of Digital Games (FDG-2014). New York, NY: ACM (7 pages).


A potentially promising application for procedural content generation (PCG) is collecting games, i.e. games in which the player strives to collect as many classes of possible artifacts as possible from a diverse set. However, the challenge for PCG in collecting games is that procedurally generated content on its own does not fall into a prede ned set of classes, leaving no concrete quanti able measure of progress for players to follow. The main idea in this paper is to remedy this shortcoming by feeding a sample of such content into a self-organizing map (SOM) that then in e ect generates as many categories as there are nodes in the SOM.  Once thereby organized, any new content discovered by a player can be categorized simply by identifying the node most activate after its presentation. This approach is tested in this paper in the Petalz video game, where 80 categories for user-bred  owers are generated by a SOM, allowing players to track their progress in discovering all the "species" that are now explicitly identi ed. The hope is that this idea will inspire more researchers in PCG to investigate applications to collecting games in the future.