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Intelligent interactive narrative systems coordinate a cast of non-player characters to make the overall story experience meaningful for the player. Narrative generation involves a tradeoff between plot-structure requirements and quality of character behavior, as well as computational efficiency. We study this tradeoff using the example of benchmark problems for narrative planning algorithms. A typical narrative planning problem calls for a sequence of actions that leads to an overall plot goal being met, while also requiring each action to respect constraints that create the appearance of character autonomy. We consider simplified solution definitions that enforce only plot requirements or only character requirements, and we measure how often each of these definitions leads to a solution that happens to meet both types of requirements—i.e., the density with which narrative plans occur among plot- or character-requirement-satisfying sequences. We then investigate whether solution densities can guide the selection of narrative planning algorithms. We compare the performance of two search strategies: one that satisfies plot requirements first and checks character requirements afterward, and one that continuously verifies character requirements. Our results show that comparing solution densities does not by itself predict which of these search strategies will be more efficient in terms of search nodes visited, suggesting that other important factors exist. We discuss what some of these factors could be. Our work opens further investigation into characterizing narrative planning algorithms and how they interact with specific domains. The results also highlight the diversity and difficulty of solving narrative planning problems.
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This content will become publicly available on December 19, 2025
Building Visual Novels with Social Simulation and Storylets
Simulationist interactive narrative systems allow game makers to craft reactive stories driven by simulated characters and their social dynamics. These systems produce narrative experiences that feel more emergent but may lack a coherent plot structure. We explored how to combine the emergent possibilities of social simulation with a procedural narrative system that affords writers strong authorial control over the plot. We did this by developing a Unity extension called Anansi that helps people create social simulation-driven visual novels. It enables users to inject simulation data into their story dialogue using logical queries and parameterized storylets written using Ink. The paper describes an overview of our extension and how we empower writers to drive narrative progression using cascading social effects from player choices.
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- Award ID(s):
- 2202521
- PAR ID:
- 10590910
- Publisher / Repository:
- Springer Nature Switzerland
- Date Published:
- Volume:
- 15468
- Page Range / eLocation ID:
- 145 to 161
- Subject(s) / Keyword(s):
- Storylets Tools Social Simulation Unity Visual Novel
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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