用可调节抽象层级构建叙事空间，让作者掌控AI生成的互动故事走向。
WhatELSE: Shaping Narrative Spaces at Configurable Level of Abstraction for AI-bridged Interactive Storytelling
- 基于示例故事生成叙事可能性空间，支持多层级抽象控制。
- 用户研究显示作者能有效感知并编辑叙事空间，游戏时生成内容有趣且连贯。
- 适合想精准控制AI生成故事方向的创作者和互动叙事开发者。
生成式AI通过即时内容生成显著提升了互动叙事（IN）中的玩家自主性，使其能根据玩家行为动态调整剧情。然而，将生成任务交由AI后，作者难以把控最终故事所处的叙事可能性空间。本文提出WhatELSE，一个基于AI的互动叙事创作系统，通过示例故事构建叙事空间，并提供叙事枢纽、概要与变体三种视图，配合语言抽象技术帮助作者理解并控制叙事边界。该系统采用创新的LLM叙事规划方法，将叙事空间展开为可执行的游戏事件。通过12名用户的实验和技术评估发现，WhatELSE使作者能够感知并编辑叙事空间，在游戏过程中生成引人入胜的互动叙事。
原文摘要 · Abstract (English)
Generative AI significantly enhances player agency in interactive narratives (IN) by enabling just-in-time content generation that adapts to player actions. While delegating generation to AI makes IN more interactive, it becomes challenging for authors to control the space of possible narratives - within which the final story experienced by the player emerges from their interaction with AI. In this paper, we present WhatELSE, an AI-bridged IN authoring system that creates narrative possibility spaces from example stories. WhatELSE provides three views (narrative pivot, outline, and variants) to help authors understand the narrative space and corresponding tools leveraging linguistic abstraction to control the boundaries of the narrative space. Taking innovative LLM-based narrative planning approaches, WhatELSE further unfolds the narrative space into executable game events. Through a user study (N=12) and technical evaluations, we found that WhatELSE enables authors to perceive and edit the narrative space and generates engaging interactive narratives at play-time.
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