22 citations · 42 across the 7 of their papers we have counts for
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3 papers · 1 filter
cs.LG2020★ 2 cited
Conditional Level Generation and Game Blending
Anurag Sarkar, Zhihan Yang, Seth Cooper
Prior research has shown variational autoencoders (VAEs) to be useful for generating and blending game levels by learning latent representations of existing level data. We build on…
cs.LG2020★ 4 cited
Game Level Clustering and Generation using Gaussian Mixture VAEs
Zhihan Yang, Anurag Sarkar, Seth Cooper
Variational autoencoders (VAEs) have been shown to be able to generate game levels but require manual exploration of the learned latent space to generate outputs with desired attri…
cs.LG2020★ 22 cited
Controllable Level Blending between Games using Variational Autoencoders
Anurag Sarkar, Zhihan Yang, Seth Cooper
Previous work explored blending levels from existing games to create levels for a new game that mixes properties of the original games. In this paper, we use Variational Autoencode…