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CORR
2016
Springer

Toward Game Level Generation from Gameplay Videos

4 years 6 months ago
Toward Game Level Generation from Gameplay Videos
Algorithms that generate computer game content require game design knowledge. We present an approach to automatically learn game design knowledge for level design from gameplay videos. We further demonstrate how the acquired design knowledge can be used to generate sections of game levels. Our approach involves parsing video of people playing a game to detect the appearance of patterns of sprites and utilizing machine learning to build a probabilistic model of sprite placement. We show how rich game design information can be automatically parsed from gameplay videos and represented as a set of generative probabilistic models. We use Super Mario Bros. as a proof of concept. We evaluate our approach on a measure of playability and stylistic similarity to the original levels as represented in the gameplay videos. Categories and Subject Descriptors I.2.1 [Artificial Intelligence]: Applications and Expert Systems— Games General Terms Algorithms, Human Factors Keywords Procedural content ...
Matthew Guzdial, Mark Riedl
Added 31 Mar 2016
Updated 31 Mar 2016
Type Journal
Year 2016
Where CORR
Authors Matthew Guzdial, Mark Riedl
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