Charting the Shapes of Stories with Game Theory

TL;DR

This paper introduces a novel method using AI and game theory to analyze story structures, character incentives, and alternative plot lines, exemplified through Shakespeare's Romeo and Juliet, aiming to deepen understanding of narratives and human experiences.

Contribution

The paper presents a new interdisciplinary approach combining AI and game theory to model and analyze story structures and character decision-making.

Findings

Game-theoretic modeling reveals character incentives.

Analysis uncovers potential alternative plot lines.

Method demonstrated on Romeo and Juliet.

Abstract

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.