Abstract
This paper introduces SuSketch, a design tool for first person shooter levels. SuSketch provides the designer with gameplay predictions for two competing players of specific character classes. The interface allows the designer to work side-by-side with an artificially intelligent creator and to receive varied types of feedback such as path information, predicted balance between players in a complete playthrough, or a predicted heatmap of the locations of player deaths. The system also proactively designs alternatives to the level and class pairing, and presents them to the designer as suggestions that improve the predicted balance of the game. SuSketch offers a new way of integrating machine learning into mixed-initiative co-creation tools, as a surrogate of human play trained on a large corpus of artificial playtraces. A user study with 16 game developers indicated that the tool was easy to use, but also highlighted a need to make SuSketch more accessible and more explainable.
Abstract (translated)
URL
https://arxiv.org/abs/2103.11726
