mlsanityData to 14 Oct 2026

STORY2GAME: Generating (Almost) Everything in an Interactive Fiction Game

arXiv 2505.03547 ↗First posted 6 May 2025cs.AIcited by 4

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Abstract (arXiv)

We introduce STORY2GAME, a novel approach to using Large Language Models to generate text-based interactive fiction games that starts by generating a story, populates the world, and builds the code for actions in a game engine that enables the story to play out interactively. Whereas a given set of hard-coded actions can artificially constrain story generation, the ability to generate actions means the story generation process can be more open-ended but still allow for experiences that are grounded in a game state. The key to successful action generation is to use LLM-generated preconditions and effects of actions in the stories as guides for what aspects of the game state must be tracked and changed by the game engine when a player performs an action. We also introduce a technique for dynamically generating new actions to accommodate the player's desire to perform actions that they think of that are not part of the story. Dynamic action generation may require on-the-fly updates to the game engine's state representation and revision of previously generated actions. We evaluate the success rate of action code generation with respect to whether a player can interactively play through the entire generated story.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 8 of its 24 references that are in the map. First posted on arXiv 6 May 2025.

Builds on

8 of 24 references.

References · 8

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2018TextWorld: A Learning Environment for Text-based Gamescited by 310
  3. 2019Learning to Speak and Act in a Fantasy Text Adventure Gamecited by 122
  4. 2024Large Language Models and Games: A Survey and Roadmapcited by 93
  5. 2020Bringing Stories Alive: Generating Interactive Fiction Worldscited by 28
  6. 2024Word2World: Generating Stories and Worlds through Large Language Modelscited by 18
  7. 2024STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Modelscited by 8
  8. 2022Neural Story Planningcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.