Game of GANs: Game-Theoretical Models for Generative Adversarial Networks. (arXiv:2106.06976v3 [cs.LG] UPDATED)

Generative Adversarial Networks (GANs) have recently attracted considerable
attention in the AI community due to its ability to generate high-quality data
of significant statistical resemblance to real data. Fundamentally, GAN is a
game between two neural networks trained in an adversarial manner to reach a
zero-sum Nash equilibrium profile. Despite the improvement accomplished in GANs
in the last few years, several issues remain to be solved. This paper reviews
the literature on the game theoretic aspects of GANs and addresses …

arxiv game gans networks