Deep Neural Network Solution for Finite State Mean Field Game with Error Estimation

Abstract We discuss the numerical solution to a class of continuous time finite state mean field games. apply deep neural network (DNN) approach solving fully coupled forward and backward ordinary differential equation system that characterizes equilibrium value function probability measure game. prove error between true approximate is linear square root DNN loss function. give an example applying method solve optimal market making problem with terminal rank-based trading volume reward.