Reconstructing Persistent Worlds from Narratives for Narrative-Grounded Interactive Experiences
Quick Answer
This study presents a novel approach to reconstructing persistent worlds from narrative descriptions, enhancing interactive experiences.
Quick Take
By developing a prototype that maintains entities, locations, and relationships, the authors demonstrate coherent gameplay grounded in narratives across various case studies, bridging computational narrative understanding and interactive content generation.
Key Points
- The approach explicitly reconstructs persistent entities and locations from narratives.
- A prototype was developed to create playable tile-based environments.
- Three case studies validate the feasibility of this reconstruction method.
- The work supports AI-assisted game authoring and educational simulations.
- It bridges computational narrative understanding with interactive content generation.
DeepSignal Analysis
What happened
The study introduces a method for reconstructing persistent worlds from narrative descriptions, aiming to improve interactive experiences. A prototype was developed to maintain entities, locations, and relationships, demonstrating coherent gameplay through various case studies, including a procedural scenario and an original fantasy narrative.
Key evidence
- The authors focus on reconstructing explicit persistent worlds from narrative descriptions, rather than treating the world as an implicit by-product of other generation tasks.
- A reference prototype was created to reconstruct structured persistent world representations, which were then used to instantiate playable tile-based environments.
- Three case studies were conducted, including a procedural scenario, an original fantasy narrative, and an adapted public-domain story, showcasing the feasibility of this approach.
Why it matters
This research addresses the challenges of aligning interactive content with narrative worlds, which is often labor-intensive. By explicitly reconstructing persistent worlds, the study provides a foundation for various applications, such as AI-assisted game authoring and educational simulations, potentially streamlining the development of narrative-driven interactive experiences.
Paper Resources
📖 Reader Mode
~2 min readAbstract:Designing narrative-grounded interactive experiences remains labor-intensive because interactive content must align with the underlying world implied by the narrative. Existing approaches formulate problems such as narrative planning, scene generation, and gameplay generation, each constructing computational representations tailored to specific downstream tasks rather than explicitly reconstructing and maintaining the persistent world that grounds them.
We investigate reconstructing explicit persistent worlds from narrative descriptions as the central computational objective for narrative-grounded interactive realization. Rather than treating the world as an implicit by-product of downstream generation, our approach reconstructs and maintains persistent entities, locations, semantic relationships, and evolving world states while inferring only the contextual information required to support coherent interactive experiences.
To investigate this perspective, we develop a reference prototype that reconstructs structured persistent world representations from narrative descriptions and subsequently instantiates playable tile-based environments. Through three representative case studies spanning a procedural scenario, an original fantasy narrative, and an adapted public-domain story, we demonstrate the feasibility of reconstructing persistent worlds and show how a shared world representation supports coherent gameplay while remaining grounded in the source narrative.
By explicitly reconstructing persistent worlds prior to interactive realization, this work bridges computational narrative understanding and interactive content generation, providing a semantic foundation for AI-assisted game authoring, mixed-initiative design, educational simulations, and narrative-grounded interactive experiences.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Graphics (cs.GR); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2608.04037 [cs.CL] |
| (or arXiv:2608.04037v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.04037 arXiv-issued DOI via DataCite |
Submission history
From: Yi-Chun Chen [view email]
[v1]
Mon, 3 Aug 2026 20:06:13 UTC (2,391 KB)
— Originally published at arxiv.org
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