Computational Solutions To The Exponential Problem in Longform Branching Interactive Digital Narratives

The proposal is to explore computational approaches to solving the exponential problem for content creation in branching digital narratives. Branching is one popular way of allowing player autonomy to be expressed in an interactive experience (whether it be a kinetic novel formed mainly of text, or a video game). In a branching narrative, each time a branch is added to an existing branch, it increases the workload of authorship exponentially. If a story has two branches, and each of those branches has two branches and so on, after just ten choices, 1024 nodes would need to be written. This exponential problem strongly limits the amount of compounded branching that can occur in a narrative.

There are a number of existing structural solutions to this problem which can be modelled. These include structures that frequently merge after branching, or use state tracking for delayed branching. These approaches can be seen in most existing branching narratives. Beyond these structural solutions, there are also promising computational approaches. Using an AI narrative director is one possibility. Another is setting up procedural rules for characters and environments so narratives can emerge in a more sandbox environment. The intention is to research the various existing solutions to the branching problem, and explore how generative techniques might extend them.