Regarding GAN training:

At each training iteration, the discriminator is trained like a normal binary classifier, then the generator is trained to minimize the discriminator's error.

A At each training iteration, the discriminator is trained like a normal binary classifier, then the generator is trained to maximize the discriminator's error.

Training GANs is simple, because of the lack of dynamics between the generator and the discriminator.