Publisher Summary This chapter describes feedforward neural networks as approximators
and relates them to statistical discriminant functions, and explains the ways in which neural
nets of varying complexity can represent equilibria in two repeated games and one dynamic
economic model. Because linear strategies are simple to implement, a large class of
equilibrium outcomes can be represented with simple perceptions. However, in the
presence of imperfect monitoring, the linear proxies can overestimate the hidden variables …