AAAI Publications, Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference

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Game Level Generation from Gameplay Videos
Matthew Guzdial, Mark Riedl

Last modified: 2016-09-19


We present an unsupervised process to generate full video game levels from a model trained on gameplay video. The model represents probabilistic relationships between shapes properties, and relates the relationships to stylistic variance within a domain. We utilize the classic platformer game Super Mario Bros. to evaluate this process due to its highly-regarded level design. We evaluate the output in comparison to other data-driven level generation techniques via a user study and demonstrate its ability to produce novel output more stylistically similar to exemplar input.


procedural content generation; machine learning; game ai

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