  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.
