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.

通过与大型语言模型的互动，玩家能够参与游戏叙事的演化，发现有趣且具有吸引力的新节点，进而创造出非原始叙事中不存在的内容。

LLM 驱动的游戏叙事中的玩家驱动新生

Player-Driven Emergence in LLM-Driven Game Narrative

This paper explores the intersection of Otome Culture and artificial
intelligence, particularly focusing on how Otome-oriented games fulfill the
emotional needs of young women. These games, which are deeply rooted in a
subcultural understanding of love, provide players with feelings of
satisfaction, companionship, and protection through carefully crafted narrative
structures and character development. With the proliferation of Large Language
Models (LLMs), there is an opportunity to transcend traditional static game
narratives and create dynamic, emotionally responsive interactions. We present
a case study of Tears of Themis, where we have integrated LLM technology to
enhance the interactive experience. Our approach involves augmenting existing
game narratives with a Question and Answer (QA) system, enriched through data
augmentation and emotional enhancement techniques, resulting in a chatbot that
offers realistic and supportive companionship.

该研究探讨了乙女文化和人工智能的交叉点，特别关注乙女导向游戏如何满足年轻女性的情感需求。这些游戏通过精心构建的叙事结构和角色发展，提供玩家满足感、陪伴感和保护感。通过整合大型语言模型（LLM）技术来增强互动体验，我们以《泪水之女神》为案例研究，将现有游戏叙事与问题 - 回答（QA）系统相结合，并通过数据增强和情感增强技术来丰富聊天机器人的功能，为玩家提供逼真且支持性的陪伴。