Consider the following value function of the initial GAN
$V(D, G) = \mathbb{E}_{x \sim p_{data(x)}} [\log D(x)] + \mathbb{E}_{z \sim p_z(z)} [1- \log D(G(z))]$
The min-max game on the value function: $min_{G} max_{D} V(D, G)$ ensures global optima. And finally $D(x) = 1/2$ for all $x$.
The paper provides the proof for attaining the convergence for $V(D, G)$.
After the paper, several GANs have been proposed and are using different value functions. So, I am wondering whether all the new value functions need to obey the mathematical properties of the initial $V(D, G)$ mentioned above so that the min-max game leads to the convergence point?