  We present a method for using neural networks to model evolutionary
population dynamics, and draw parallels to recent deep learning advancements in
which adversarially-trained neural networks engage in coevolutionary
interactions. We conduct experiments which demonstrate that models from
evolutionary game theory are capable of describing the behavior of these neural
population systems.
