Latent Combinational Game Design

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 G...

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Veröffentlicht in:IEEE transactions on games Jg. 16; H. 3; S. 659 - 669
Hauptverfasser: Sarkar, Anurag, Cooper, Seth
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2024
Schlagworte:
Aerospace electronics
Combinational creativity
Creativity
Decoding
game blending
Games
Layout
procedural content generation
Training
Training data
variational autoencoder (VAE)
ISSN:2475-1502, 2475-1510
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Zusammenfassung: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 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.
ISSN:2475-1502
2475-1510
DOI:10.1109/TG.2023.3346331