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Interactive narrative in games utilize a combination of dynamic adaptability and predefined story elements to support player agency and enhance player engagement. However, crafting such narratives requires significant manual authoring and coding effort to translate scripts to playable game levels. Advances in pretrained large language models (LLMs) have introduced the opportunity to procedurally generate narratives. This paper presents NarrativeGenie, a framework to generate narrative beats as a cohesive, partially ordered sequence of events that shapes narrative progressions from brief natural language instructions. By leveraging LLMs for reasoning and generation, NarrativeGenie, translates a designer’s story overview into a partially ordered event graph to enable player-driven narrative beat sequencing. Our findings indicate that NarrativeGenie can provide an easy and effective way for designers to generate an interactive game episode with narrative events that align with the intended story arc while at the same time granting players agency in their game experience. We extend our framework to dynamically direct the narrative flow by adapting real-time narrative interactions based on the current game state and player actions. Results demonstrate that NarrativeGenie generates narratives that are coherent and aligned with the designer’s vision.
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This content will become publicly available on November 7, 2026
Structure, Agency, and Improvisation in Human-Led Digital Interactive Narrative Exercises
Supporting high-agency player experiences without compromising narrative control is one of the major challenges in digital interactive narrative design. Humans, on the other hand, frequently meet this challenge when cooperating to improvise a narrative. We present a study examining how humans improvise narratives when paired together as the player and game master of a digital interactive narrative. We collected gameplay logs from these experiences, as well as participants’ reported perceptions of narrative structure, personal agency, and the reasons for both their choices and their partners’. We found a strong link between perceptions of structure and of agency. We also found a tendency for participants to better identify the goals of their partner’s actions following sessions where game masters expressed higher agency. Finally, we characterize the experiences using principles of improv theatre, drawing from the data to analyze negative experiences of agency as failures in the improv partnership.
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- Award ID(s):
- 2145153
- PAR ID:
- 10676444
- Publisher / Repository:
- Association for the Advancement of Artificial Intelligence
- Date Published:
- Journal Name:
- Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
- Volume:
- 21
- Issue:
- 1
- ISSN:
- 2326-909X
- Page Range / eLocation ID:
- 237 to 246
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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