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Paper · arXiv 2504.14538

BookWorld: From Novels to Interactive Agent Societies for Creative Story Generation

Yiting Ran, Xintao Wang, Tian Qiu, Jiaqing Liang, Yanghua Xiao, Deqing Yang

30 upvotesApril 20, 2025arXiv 预印本
AI 摘要

BookWorld, a system for simulating multi-agent societies based on books, generates high-quality, faithful stories and supports applications like story generation and social simulation.

large language modelsLLMsmulti-agent systemsBookWorldbook-based simulationscharactersfictional worldviewsgeographical constraintsstory generationinteractive gamessocial simulation

Abstract

Recent advances in large language models (LLMs) have enabled social simulation through multi-agent systems. Prior efforts focus on agent societies created from scratch, assigning agents with newly defined personas. However, simulating established fictional worlds and characters remain largely underexplored, despite its significant practical value. In this paper, we introduce BookWorld, a comprehensive system for constructing and simulating book-based multi-agent societies. BookWorld's design covers comprehensive real-world intricacies, including diverse and dynamic characters, fictional worldviews, geographical constraints and changes, e.t.c. BookWorld enables diverse applications including story generation, interactive games and social simulation, offering novel ways to extend and explore beloved fictional works. Through extensive experiments, we demonstrate that BookWorld generates creative, high-quality stories while maintaining fidelity to the source books, surpassing previous methods with a win rate of 75.36%. The code of this paper can be found at the project page: https://bookworld2025.github.io/.

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