StoryBox: Collaborative Multi-Agent Simulation for Hybrid Bottom-Up Long-Form Story Generation Using Large Language Models

• URL: http://arxiv.org/abs/2510.11618v1
• Date: Mon, 13 Oct 2025 16:57:32 GMT
• Title: StoryBox: Collaborative Multi-Agent Simulation for Hybrid Bottom-Up Long-Form Story Generation Using Large Language Models
• Authors: Zehao Chen, Rong Pan, Haoran Li,
• Abstract summary: We propose a novel approach to long-form story generation, termed hybrid bottom-up long-form story generation.<n>In our method, agents interact within a dynamic sandbox environment, where their behaviors and interactions with one another and the environment generate emergent events.
• Score: 15.245564064908903
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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