Procedural Content Generation of Puzzle Games using Conditional Generative Adversarial Networks

Andreas Hald, Jens Stuckermann Hansen, Jeppe Theiss Kristensen, Paolo Burelli

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


In this article, we present an experimental approach to using parameterized Generative Adversarial Networks (GANs) to produce levels for the puzzle game Lily’s Garden1. We extract two condition-vectors from the real levels in an effort to control the details of the GAN’s outputs. While the GANs performs well in approximating the first condition (map-shape), they struggle to approximate the second condition (piece distribution). We hypothesize that this might be improved by trying out alternative architectures for both the Generator and Discriminator of the GANs.
Original languageEnglish
Title of host publicationFDG '20: International Conference on the Foundations of Digital Games
PublisherAssociation for Computing Machinery
Publication date2020
Article number99
ISBN (Electronic)9781450388078
Publication statusPublished - 2020
EventFDG 2020: Foundations of Digitale Games - Malta, Malta
Duration: 16 Sept 202018 Sept 2020
Conference number: 2020


ConferenceFDG 2020: Foundations of Digitale Games
Internet address


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