Discrete-time hybrid control with risk-sensitive discounted costs

This paper studies discrete-time hybrid control problems where the controller’s payoff function follows a risk-sensitive discounted model. The associated discount factor can depend on state and action variables, which can even take values of zero or one. We prove the existence of optimal control policies under two different hypotheses. The following technique is the dynamic programming method, where we characterize the minimum cost as the solution of the so-called dynamic programming equations and find the above optimal policies through these equations. We illustrate our theory with practical examples involving inventory-manufacturing systems, and pollution management.