Finite State Dynamic Games with Asymmetric Information: A Framework for Applied Work

With applied work in mind, we define an equilibrium notion for dynamic games with asymmetric information which does not require a specification for players' beliefs about their opponent types. This enables us to define equilibrium conditions which, at least in principal, are testable and can be computed using a simple reinforcement learning algorithm. We conclude with an example that endogenizes the maintenance decisions for electricity generators in a dynamic game among electric utilities in which the costs states of the generators are private information.