Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning

26 May 2020Vanessa VolzNiels JustesenSam SnodgrassSahar AsadiSami PurmonenChristoffer HolmgårdJulian TogeliusSebastian Risi

Recent procedural content generation via machine learning (PCGML) methods allow learning from existing content to produce similar content automatically. While these approaches are able to generate content for different games (e.g. Super Mario Bros., DOOM, Zelda, and Kid Icarus), it is an open questions how well these approaches can capture large-scale visual patterns such as symmetry... (read more)

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