  In this paper, we introduce an imagine network that can simulate itself
through artificial association networks. Association, deduction, and memory
networks are learned, and a network is created by combining the discriminator
and reinforcement learning models. This model can learn various datasets or
data samples generated in environments and generate new data samples.
