Title :
Approximating Ergodic Average Reward Continuous-Time Controlled Markov Chains
Author :
Prieto-Rumeau, Tomás ; Lorenzo, Jos éMaría
Author_Institution :
Dept. of Stat. & Oper. Res., UNED, Madrid, Spain
Abstract :
We study the approximation of an ergodic average reward continuous-time denumerable state Markov decision process (MDP) by means of a sequence of MDPs. Our results include the convergence of the corresponding optimal policies and the optimal gains. For a controlled upwardly skip-free process, we show some computational results to illustrate the convergence theorems.
Keywords :
Markov processes; continuous time systems; convergence; optimal control; Markov decision process; convergence theorems; ergodic average reward continuous-time control; optimal gains; optimal policies; Adaptive control; Convergence; Operations research; Optimal control; Process control; State-space methods; Statistics; Terminology; Approximation of control problems; Ergodic Markov decision processes (MDPs); policy iteration algorithm;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2009.2033848
