用多智能体模拟生成超过1万字的自然连贯长篇故事
StoryBox: Collaborative Multi-Agent Simulation for Hybrid Bottom-Up Long-Form Story Generation Using Large Language Models
- 让角色在动态环境中自主互动，自动生成故事情节
- 生成故事超1万字仍保持连贯性，性能达当前最佳
- 适合需要自发剧情发展的创作场景
人类创作者常从整体情境出发，设想角色与环境的互动。受此启发，我们提出一种新型长篇故事生成方法——混合自下而上的故事生成，基于多智能体仿真。在该方法中，智能体在动态沙盒环境中交互，其行为及相互作用与环境共同催生出涌现事件，这些事件成为故事基础，推动角色发展与情节自然演进。与传统自上而下的强结构方法不同，本方法使事件自发展开，增强叙事的自发性与吸引力。系统可生成超过10,000字的故事，同时保持语义连贯与一致性，有效解决现有模型在长文本生成中的关键挑战。在多个指标上达到当前最优表现。该方法为生成动态、沉浸式长篇故事提供了可扩展且创新的解决方案。
原文摘要 · Abstract (English)
Human writers often begin their stories with an overarching mental scene, where they envision the interactions between characters and their environment. Inspired by this creative process, we propose a novel approach to long-form story generation, termed hybrid bottom-up long-form story generation, using multi-agent simulations. In our method, agents interact within a dynamic sandbox environment, where their behaviors and interactions with one another and the environment generate emergent events. These events form the foundation for the story, enabling organic character development and plot progression. Unlike traditional top-down approaches that impose rigid structures, our hybrid bottom-up approach allows for the natural unfolding of events, fostering more spontaneous and engaging storytelling. The system is capable of generating stories exceeding 10,000 words while maintaining coherence and consistency, addressing some of the key challenges faced by current story generation models. We achieve state-of-the-art performance across several metrics. This approach offers a scalable and innovative solution for creating dynamic, immersive long-form stories that evolve organically from agent-driven interactions.
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