Bootstrapping Conditional GANs for Video Game Level Generation

Understand

Generative Adversarial Networks (GANs) have shown im-pressive results for image generation.

• However, GANs facechallenges in generating contents with certain types of con-straints, such as game levels.
• Specifically, it is difficult togenerate levels that have aesthetic appeal and are playable atthe same time.
• Additionally, because training data usually islimited, it is challenging to generate unique levels with cur-rent GANs.