Personalized Quest and Dialogue Generation in Role-Playing Games: A Knowledge Graph- and Language Model-based Approach

要旨

Procedural content generation (PCG) in video games offers unprecedented opportunities for customization and user engagement. Working within the specialized context of role-playing games (RPGs), we introduce a novel framework for quest and dialogue generation that places the player at the core of the generative process. Drawing on a hand-crafted knowledge base, our method grounds generated content with in-game context while simultaneously employing a large-scale language model to create fluent, unique, accompanying dialogue. Through human evaluation, we confirm that quests generated using this method can approach the performance of hand-crafted quests in terms of fluency, coherence, novelty, and creativity; demonstrate the enhancement to the player experience provided by greater dynamism; and provide a novel, automated metric for the relevance between quest and dialogue. We view our contribution as a critical step toward dynamic, co-creative narrative frameworks in which humans and AI systems jointly collaborate to create unique and user-specific playable experiences.

著者
Trevor Ashby
Brigham Young University, Provo, Utah, United States
Braden K. Webb
Brigham Young University, Provo, Utah, United States
Gregory Knapp
Brigham Young University, Provo, Utah, United States
Jackson Searle
Brigham Young University, Provo, Utah, United States
Nancy Fulda
Brigham Young University, Provo, Utah, United States
論文URL

https://doi.org/10.1145/3544548.3581441

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Games beyond Gaming

Room Y03+Y04
6 件の発表
2023-04-24 23:30:00
2023-04-25 00:55:00