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Procedural Content Generation of Puzzle Games using Conditional Generative Adversarial Networks

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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
DOIs
Publication statusPublished - 2020
EventFoundations of Digital Games - Malta
Duration: 15 Sep 202018 Sep 2020
http://fdg2020.org

Conference

ConferenceFoundations of Digital Games
LocationMalta
Periode15/09/202018/09/2020
Internetadresse

ID: 85512878