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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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Academical: A Dynamic Interactive Narrative Game for Responsible Conduct of Research Training
Our demo showcases a choice-based interactive narrative game created to teach responsible conduct of research and research ethics. It re-imagines the experience of a game previously published in the literature, using a content-selection system that dynamically constructs dialogue choices during play. Our goal is to provide players with more opportunities to experience agency than they would have with the original game’s hand-authored branching narrative structure. Primarily, our system implements a conversation thread-switching mechanic that allows players to fluidly enter/exit conversation topics as one would in a real-life conversation.
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- Award ID(s):
- 2202521
- PAR ID:
- 10539227
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5067-8
- Page Range / eLocation ID:
- 1 to 2
- Subject(s) / Keyword(s):
- Education Training Ethics Responsible Conduct of Research Interactive Narrative AI
- Format(s):
- Medium: X
- Location:
- Milan, Italy
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CoG60054.2024.10645569
