- Conference Paper
This paper considers discrete-time constrained Markov control processes (MCPs) under the long-run expected average cost optimality criterion. For Borel state and action spaces a two-step method is presented to numerically approximate the optimal value of this constrained MCPs. The proposed method employs the infinite-dimensional linear programming (LP) representation of the constrained MCPs. In particular, we establish a bridge from the infinite-dimensional LP characterization to a finite LP consisting of a first asymptotic step and a second step that provides explicit bounds on the approximation error. Finally, the applicability and performance of the theoretical results are demonstrated on an LQG example. Show more
Book title2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)
Pages / Article No.
Organisational unit03751 - Lygeros, John / Lygeros, John
MoreShow all metadata