Predicting User Choices in Interactive Narratives using Indexter’s Pairwise Event Salience Hypothesis

Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that when a past event shares one or more of these indices with the most recently narrated event, that past event is more salient, or easier to recall, than an event which shares none of them. In this study we demonstrate that we can predict user choices based on the salience of past events. Specifically, we investigate the hypothesis that when users are given a choice between two events in an interactive narrative, they are more likely to choose the one which makes the previous events in the story more salient according to this theory.

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Rachelyn Farrell, Stephen G. Ware. Predicting user choices in interactive narratives using Indexter’s pairwise event salience hypothesis. In Proceedings of the 9th International Conference on Interactive Digital Storytelling, pp. 147-155, 2016.

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Fast and Diverse Narrative Planning through Novelty Pruning

Novelty pruning is a simple enhancement that can be added to most planners. A node is removed unless it is possible to find a set of n literals which are true in the current state and have never all been true in any of that plan’s previous states. Expanding on the success of the Iterated Width algorithm in classical planning and general game playing, we apply this technique to narrative planning. Using a suite of 8 benchmark narrative planning problems, we demonstrate that novelty pruning can be used with breadth-first search to solve smaller problems optimally and combined with heuristic search to solve larger problems faster. We also demonstrate that when many solutions to the same problem are generated, novelty pruning can produce a wider variety of solutions in some domains.

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Rachelyn Farrell, Stephen G. Ware. Fast and diverse narrative planning through novelty pruning. In Proceedings of the 12th AAAI International Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 37-43, 2016.

[bibtex]