# Player-Driven Emergence in LLM-Driven Game Narrative

arXiv: https://arxiv.org/abs/2404.17027 · HTML: https://mlsanity.com/paper/2404.17027/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 31 references that are in the map.
- First posted on arXiv 25 Apr 2024.

## Builds on (most cited first, 16 of 16)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Voyager: An Open-Ended Embodied Agent with Large Language Models](https://mlsanity.com/paper/2305.16291/) (2023)
- [TextWorld: A Learning Environment for Text-based Games](https://mlsanity.com/paper/1806.11532/) (2018)
- [Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf](https://mlsanity.com/paper/2309.04658/) (2023)
- [Playing repeated games with Large Language Models](https://mlsanity.com/paper/2305.16867/) (2023)
- [Interactive Fiction Games: A Colossal Adventure](https://mlsanity.com/paper/1909.05398/) (2019)
- [Learning to Speak and Act in a Fantasy Text Adventure Game](https://mlsanity.com/paper/1903.03094/) (2019)
- [Keep CALM and Explore: Language Models for Action Generation in Text-based Games](https://mlsanity.com/paper/2010.02903/) (2020)
- [Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers](https://mlsanity.com/paper/2211.05030/) (2022)
- [Level Generation Through Large Language Models](https://mlsanity.com/paper/2302.05817/) (2023)
- [On the Creativity of Large Language Models](https://mlsanity.com/paper/2304.00008/) (2023)
- [Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions](https://mlsanity.com/paper/2304.02868/) (2023)
- [Practical PCG Through Large Language Models](https://mlsanity.com/paper/2305.18243/) (2023)
- [Generalization in Text-based Games via Hierarchical Reinforcement Learning](https://mlsanity.com/paper/2109.09968/) (2021)
- [Perceiving the World: Question-guided Reinforcement Learning for Text-based Games](https://mlsanity.com/paper/2204.09597/) (2022)
- [Dialogue Shaping: Empowering Agents through NPC Interaction](https://mlsanity.com/paper/2307.15833/) (2023)

## Built on by (most cited first, 16 of 16)

- [GPT for Games: An Updated Scoping Review (2020-2024)](https://mlsanity.com/paper/2411.00308/) (2024)
- [Collaborative Quest Completion with LLM-driven Non-Player Characters in Minecraft](https://mlsanity.com/paper/2407.03460/) (2024)
- [WhatELSE: Shaping Narrative Spaces at Configurable Level of Abstraction for AI-bridged Interactive Storytelling](https://mlsanity.com/paper/2502.18641/) (2025)
- [LLM-Driven NPCs: Cross-Platform Dialogue System for Games and Social Platforms](https://mlsanity.com/paper/2504.13928/) (2025)
- [Game Plot Design with an LLM-powered Assistant: An Empirical Study with Game Designers](https://mlsanity.com/paper/2411.02714/) (2024)
- [Leveraging Large Language Models for Active Merchant Non-player Characters](https://mlsanity.com/paper/2412.11189/) (2024)
- [AI for Games in the Foundation Model Era](https://mlsanity.com/paper/2609.16679/) (2026)
- [Automatic Bug Detection in LLM-Powered Text-Based Games Using LLMs](https://mlsanity.com/paper/2406.04482/) (2024)
- [Guiding Generative Storytelling with Knowledge Graphs](https://mlsanity.com/paper/2505.24803/) (2025)
- [Shall We Play a Game? Language Models for Open-ended Wargames](https://mlsanity.com/paper/2509.17192/) (2025)
- [Can LLM Agents Stick to the Script? A Benchmark for Long-Horizon Consistency in Interactive Narratives](https://mlsanity.com/paper/2608.08160/) (2026)
- [Narrative Context Protocol: An Open-Source Storytelling Framework for Generative AI](https://mlsanity.com/paper/2503.04844/) (2025)
- [How LLMs are Shaping the Future of Virtual Reality](https://mlsanity.com/paper/2508.00737/) (2025)
- [FAIRGAMER: Evaluating Social Biases in LLM-Based Video Game NPCs](https://mlsanity.com/paper/2508.17825/) (2025)
- [Aligning Large Language Models with Procedural Rules: An Autoregressive State-Tracking Prompting for In-Game Trading](https://mlsanity.com/paper/2510.25014/) (2025)
- [AI Native Games: A Survey and Roadmap](https://mlsanity.com/paper/2607.00527/) (2026)

## Abstract (arXiv)

We explore how interaction with large language models (LLMs) can give rise to emergent behaviors, empowering players to participate in the evolution of game narratives. Our testbed is a text-adventure game in which players attempt to solve a mystery under a fixed narrative premise, but can freely interact with non-player characters generated by GPT-4, a large language model. We recruit 28 gamers to play the game and use GPT-4 to automatically convert the game logs into a node-graph representing the narrative in the player's gameplay. We find that through their interactions with the non-deterministic behavior of the LLM, players are able to discover interesting new emergent nodes that were not a part of the original narrative but have potential for being fun and engaging. Players that created the most emergent nodes tended to be those that often enjoy games that facilitate discovery, exploration and experimentation.