GAN

Generative Adversarial Network — a framework where a generator network learns to produce realistic samples by competing against a discriminator network that tries to distinguish generated from real samples. In robotics, GANs are used for domain adaptation (translating simulated images to look real), data augmentation, and adversarial imitation learning (GAIL).