Efficient choice enumeration for narrative world design
An open challenge for AI in digital games is narrative experience management, the problem of automatically directing virtual characters in an interactive story to produce specific narrative effects for human participants. One important aspect of interactive narrative quality is participant choice, which provides the central distinction between interactive and linear storytelling. Most experience management work identifies storytelling patterns an agent should value or guides participants through high-value story trajectories. However, the types and quality of choices available in an interactive story are influenced not only by a model of narrative and specific story character actions, but also the world design that affords situations and actions. In this paper, we present a method for generating all unique, accessible choice combinations for a story world as a first step towards experience-driven interactive narrative world design. We benchmark the approach against several baselines and discuss its use as a tool for human and automated world designers.
