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Psychological research has demonstrated that as we experience a story several features affect the salience of its events in memory. These features correspond to who? where? when? how? and why? questions about those events. Computational models of salience have been used in interactive narratives to measure which events people most easily remember from the past and which they expect more readily from the future. We use three example domains to show that events in sequences that are solutions to narrative planning problems are generally more salient with each other, and events in non-solution sequences are less salient with each other. This means that measuring the salience of a sequence of actions during planning can serve as an efficient cost function to improve the speed, and perhaps also the quality, of a narrative planner.
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Generating Explorable Narrative Spaces with Answer Set Programming
Previous approaches to narrative generation have required a new planner implementation for each set of constraints deemed relevant to the narrative domain, each consisting of thousands of lines of code and supporting one primary mode of interaction: fully specifying a domain and problem, and receiving a plan as output. We present a lightweight, flexible narrative planner written with Answer Set Programming, designed specifically to support constraint-based narrative generation, show how it generalizes previous approaches, and show how it can be easily extended with notions of thematic plot schema such as “betrayal.” Finally, we demonstrate how the ASP model can be explored through interactive question answering, where answers take the form of generated narratives. In the long term, we intend this work to support understanding of complex rule systems through interactive exploration.
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- Award ID(s):
- 1846122
- PAR ID:
- 10233629
- Editor(s):
- Lelis, Levi; Thue, David
- Date Published:
- Journal Name:
- Sixteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
- Volume:
- 16
- Issue:
- 1
- ISSN:
- 2334-0924
- Page Range / eLocation ID:
- 45-51
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
