Stories are records of our experiences and their analysis reveals insights into the nature of being human. Successful analyses are often interdisciplinary, leveraging mathematical tools to extract structure from stories and insights from structure. Historically, these tools have been restricted to one dimensional charts and dynamic social networks; however, modern AI offers the possibility of identifying more fully the plot structure, character incentives, and, importantly, counterfactual plot lines that the story could have taken but did not take. In this work, we use AI to model the structure of stories as game-theoretic objects, amenable to quantitative analysis. This allows us to not only interrogate each character's decision making, but also possibly peer into the original author's conception of the characters' world. We demonstrate our proposed technique on Shakespeare's famous Romeo and Juliet. We conclude with a discussion of how our analysis could be replicated in broader contexts, including real-life scenarios.

翻译：故事是人类经验的记录，对其分析能揭示人性的本质。成功的分析往往是跨学科的，通过数学工具从故事中提取结构，并从结构中获取洞见。历史上，这些工具仅限于一维图表和动态社交网络；然而，现代人工智能为更全面地识别情节结构、角色动机，尤其是故事本可能发生但未发生的反事实情节线提供了可能。在本研究中，我们利用人工智能将故事结构建模为博弈论对象，使其适用于定量分析。这不仅使我们能够审视每个角色的决策过程，还可能窥见原作者对角色世界的构思。我们在莎士比亚著名的《罗密欧与朱丽叶》上演示了所提出的技术。最后，我们讨论了如何在更广泛的背景（包括现实生活场景）中复现我们的分析。