StoryVerse: Towards Co-authoring Dynamic Plot with LLM-based Character Simulation via Narrative Planning
Yi Wang, Qian Zhou, David Ledo
Abstract
Automated plot generation for games enhances the player’s experience by providing rich and immersive narrative experience. Recent advancements use Large Language Models (LLMs) to drive the behavior of virtual characters, allowing plots to emerge from interactions between characters and their environments. However, the emergent nature of such decentralized plot generation makes it difficult for authors to direct plot progression. We propose a novel plot creation workflow that mediates between a writer’s authorial intent and the emergent behaviors from LLM-driven character simulations, through a novel authorial structure called “abstract acts”. Writers create high-level plot outlines which are transformed into character actions via an LLM-based narrative planning process, based on the game world state. This results in narratives co-created by the author, the simulated characters, and the player. We present StoryVerse as a proof-of-concept system to demonstrate the workflow, and showcase its versatility across various stories and game environments.