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Procedural Generation of Narrative Worlds
Open accessAbstract
A narrative world typically consists of several interrelated locations that, all together, fully support enacting a given story. For this, each location in a narrative world features all the objects as required there by the narrative, as well as a variety of other objects that plausibly describe or decorate the location. Procedural generation of narrative worlds poses many challenges, including that, First, it cannot lean only on domain knowledge (e.g., patterns of objects commonly found in typical locations), and, second, it involves a temporal dimension, which introduces dynamic fluctuations of objects between locations. In this article, we present a novel approach for the procedural generation of narrative worlds, following two stages: first, anarrative world moldis generated (only once) for a given story; second, the narrative world mold is used to create one (or more) possible narrative worlds for that story. For each story, its narrative world mold integrates spatio-temporal descriptions of its locations with the object semantics and the domain knowledge previously acquired on typical locations. We describe how a narrative world mold can be generated, as well as how it can be fed to existing procedural generation methods, to create a variety of narrative worlds that fit that narrative. We evaluate our own implementation of this approach, performing a number of experiments that illustrate both the expressive power of narrative world molds and their ability to steer the generation of narrative worlds.
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“Procedural narrative generation is a widely accepted approach to this problem (Balint and Bidarra 2023; Sandhu and McCoy 2023).”
From PANGeA: Procedural Artificial Narrative Using Generative AI for Turn-Based, Role-Playing Video Games (2024) · cites this paper as Balint and Bidarra 2023
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Cited by
Sorted by citations
PANGeA: Procedural Artificial Narrative Using Generative AI for Turn-Based, Role-Playing Video Games
Buongiorno, S., Klinkert, L., Zhuang, Z., Chawla, T., & Clark, C. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v20i1.31876 · Cited by 37
Metadata
- Authors
- Balint, J. T., & Bidarra, R.
- Affiliations
- Stonehill College (US)
- Delft University of Technology, Delft, The Netherlands
- Venue
- IEEE Transactions on Games
- Published
- 2023-06
- Volume
- 15
- Issue
- 2
- Pages
- 262-272
- ISSN
- 2475-1502 (ISSN-L)
- 2475-1510
- OpenAlex
- W4312570465
- Cited by
- 11
- References
- 1
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 2 · 2023: 1
- FWCI
- 0.58
- Type
- journal article
- Language
- en
- Open access
- green
- resolver.tudelft.nl
- Licence
- Locations
- IEEE Transactions on Games (publishedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Funders
- Virtual E-Coaching and Storytelling Technology for Post-Traumatic Stress Disorder Programme
- Netherlands Organization for Scientific Research (314-99-104)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Social Sciences › Sociology and Political Science › Digital Games and Media
- Keywords
- procedural content generation, narrative worlds, object semantics, domain knowledge
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