2. Generated Opponent Network (GAN) is a deep learning model and one of the most promising unsupervised learning methods in complex distributed environment in recent years.

3. This model has produced quite good output through game learning between (at least) two modules in the framework: GenerativeModel and DiscriminativeModel. In the original GAN theory, it is not required that both g and d are neural networks, but only that they can fit the corresponding generating and discriminating functions. However, in practical applications, deep neural networks are generally used as G and D. An excellent GAN application needs a good training method, otherwise the output may be unsatisfactory due to the freedom of neural network model.