Practical PCG Through Large Language Models

Muhammad U. Nasir, Julian Togelius

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    Large Language Models (LLMs) have proven to be useful tools in various domains outside of the field of their inception, which was natural language processing. In this study, we provide practical directions on how to use LLMs to generate 2D-game rooms for an under-development game, named Metavoidal. Our technique can harness the power of GPT-3 by Human-in-the-loop fine-tuning which allows our method to create 37% Playable-Novel levels from as scarce data as only 60 hand-designed rooms under a scenario of the non-trivial game, with respect to (Procedural Content Generation) PCG, that has a good amount of local and global constraints.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 2023 IEEE Conference on Games, CoG 2023
    PublisherIEEE Computer Society
    ISBN (Electronic)9798350322774
    StatePublished - 2023
    Event5th Annual IEEE Conference on Games, CoG 2023 - Boston, United States
    Duration: Aug 21 2023Aug 24 2023

    Publication series

    NameIEEE Conference on Computatonal Intelligence and Games, CIG
    ISSN (Print)2325-4270
    ISSN (Electronic)2325-4289


    Conference5th Annual IEEE Conference on Games, CoG 2023
    Country/TerritoryUnited States


    • Large Language Models
    • Procedural Content Generation

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Graphics and Computer-Aided Design
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction
    • Software


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