Abstract
This paper studies the infinite horizon average cost Markov control model subject to ambiguity on the controlled process conditional distribution. The stochastic control problem is formulated as a minimax optimization in which, (i) the existence of optimal policies is established through a pair of canonical dynamic programming equations derived for Borel state and action spaces, and (ii) the controlled process maximizing conditional distribution is characterized through a water-filling solution derived for finite state and action spaces. To obtain average cost optimal policies numerically a policy iteration algorithm is also developed. Finally, as an application of the proposed canonical dynamic programming equations, an example is provided.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
