Markov Decision Processes: Discrete Stochastic Dynamic Programming,Used

An Uptodate, Unified And Rigorous Treatment Of Theoretical, Computational And Applied Research On Markov Decision Process Models. Concentrates On Infinitehorizon Discretetime Models. Discusses Arbitrary State Spaces, Finitehorizon And Continuoustime Discretestate Models. Also Covers Modified Policy Iteration, Multichain Models With Average Reward Criterion And Sensitive Optimality. Features A Wealth Of Figures Which Illustrate Examples And An Extensive Bibliography.