Stories from the bottom up: emergent narratives with composable story sifting patterns

Emergent Narratives (EN) are a popular approach in game design where stories naturally emerge from players' interactions with the game world. Story sifting is an EN technique where the player’s attention is drawn to particularly interesting narrative patterns, but these story sifting patterns can be complex and difficult to create. To address this, we have developed an event-based rules system that supports composable patterns: building blocks that allow higher-level stories to be constructed from lower level ones. We demonstrate our approach through a simulation (of an alien invasion scenario) alongside a powerful incremental story sifter that curates compound events. We conduct agent ratio and stability testing to demonstrate the system's robustness, and a complexity test to show how the performance of the sifter scales with agent numbers and map size. Our findings show that the system remains stable throughout. Our work demonstrates that an event-based rules approach can effectively support composite patterns, ultimately enabling the curation of more complex EN stories.

Publication Details

Journal
ePrints Soton (University of Southampton)
Published
2025-05-09
DOI
https://doi.org/10.1145/3723498.372380
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
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article

Stories from the bottom up: emergent narratives with composable story sifting patterns

ePrints Soton (University of Southampton)
Artificial Intelligence in Games
article

Stories from the bottom up: emergent narratives with composable story sifting patterns

article en

Abstract

Emergent Narratives (EN) are a popular approach in game design where stories naturally emerge from players' interactions with the game world. Story sifting is an EN technique where the player’s attention is drawn to particularly interesting narrative patterns, but these story sifting patterns can be complex and difficult to create. To address this, we have developed an event-based rules system that supports composable patterns: building blocks that allow higher-level stories to be constructed from lower level ones. We demonstrate our approach through a simulation (of an alien invasion scenario) alongside a powerful incremental story sifter that curates compound events. We conduct agent ratio and stability testing to demonstrate the system's robustness, and a complexity test to show how the performance of the sifter scales with agent numbers and map size. Our findings show that the system remains stable throughout. Our work demonstrates that an event-based rules approach can effectively support composite patterns, ultimately enabling the curation of more complex EN stories.

ePrints Soton (University of Southampton)
Openalex Percentile: Top 77%
Artificial Intelligence in Games
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Stories from the bottom up: emergent narratives with composable story sifting patterns · ePrints Soton (University of Southampton) (2025) | TGRS Research Map | TGRS