论文标题
潜在组合游戏设计
Latent Combinational Game Design
论文作者
论文摘要
我们介绍了潜在的组合游戏设计 - 一种用于生成可玩游戏的方法，该游戏使用深层生成潜伏变量模型将给定的游戏组合在一起。我们使用高斯混合物变化自动编码器（GMVAE），通过高斯组件的混合物对VAE潜在空间进行建模。通过监督的培训，每个组件都从一个游戏中编码级别，并让我们将混合游戏定义为这些组件的线性组合。这使生成新游戏混合了输入游戏，并控制混合中每个游戏的相对比例。我们还使用条件VAE进行了先前的混合工作，并与GMVAE进行比较，并另外引入了混合条件GMVAE（CGMVAE）架构，使我们能够产生整个混合级别和布局。结果表明，这些方法可以生成可玩的游戏，以在指定组合中混合输入游戏。我们使用平台游戏和基于地牢的游戏来展示我们的结果。
We present latent combinational game design -- an approach for generating playable games that blend a given set of games in a desired combination using deep generative latent variable models. We use Gaussian Mixture Variational Autoencoders (GMVAEs) which model the VAE latent space via a mixture of Gaussian components. Through supervised training, each component encodes levels from one game and lets us define blended games as linear combinations of these components. This enables generating new games that blend the input games as well as controlling the relative proportions of each game in the blend. We also extend prior blending work using conditional VAEs and compare against the GMVAE and additionally introduce a hybrid conditional GMVAE (CGMVAE) architecture which lets us generate whole blended levels and layouts. Results show that these approaches can generate playable games that blend the input games in specified combinations. We use both platformers and dungeon-based games to demonstrate our results.
