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GRIM: GRaph-based Interactive narrative visualization for gaMes

15 November 2023
Jorge Leandro
Sudha Rao
Michael Xu
Weijia Xu
Nebojsa Jojic
Chris Brockett
W. Dolan
    AI4CE
ArXiv (abs)PDFHTMLHuggingFace (13 upvotes)
Abstract

Dialogue-based Role Playing Games (RPGs) require powerful storytelling. The narratives of these may take years to write and typically involve a large creative team. In this work, we demonstrate the potential of large generative text models to assist this process. \textbf{GRIM}, a prototype \textbf{GR}aph-based \textbf{I}nteractive narrative visualization system for ga\textbf{M}es, generates a rich narrative graph with branching storylines that match a high-level narrative description and constraints provided by the designer. Game designers can interactively edit the graph by automatically generating new sub-graphs that fit the edits within the original narrative and constraints. We illustrate the use of \textbf{GRIM} in conjunction with GPT-4, generating branching narratives for four well-known stories with different contextual constraints.

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