In this paper, we discuss Markovian decision programming with recursive vector-reward andgive an algorithm to find optimal policies. We prove that: (1) There is a Markovian optimal policy for the nonstationary case; (...In this paper, we discuss Markovian decision programming with recursive vector-reward andgive an algorithm to find optimal policies. We prove that: (1) There is a Markovian optimal policy for the nonstationary case; (2) Thereis a stationary optimal policy for the stationary case.展开更多
This paper deals with the continuous time Markov decision programming (briefly CTMDP) withunbounded reward rate.The economic criterion is the long-run average reward. To the models withcountable state space,and compac...This paper deals with the continuous time Markov decision programming (briefly CTMDP) withunbounded reward rate.The economic criterion is the long-run average reward. To the models withcountable state space,and compact metric action sets,we present a set of sufficient conditions to ensurethe existence of the stationary optimal policies.展开更多
基金The project is supported by National Natural Science Foundation of China
文摘In this paper, we discuss Markovian decision programming with recursive vector-reward andgive an algorithm to find optimal policies. We prove that: (1) There is a Markovian optimal policy for the nonstationary case; (2) Thereis a stationary optimal policy for the stationary case.
基金This paper was prepared with the support of the National Youth Science Foundation
文摘This paper deals with the continuous time Markov decision programming (briefly CTMDP) withunbounded reward rate.The economic criterion is the long-run average reward. To the models withcountable state space,and compact metric action sets,we present a set of sufficient conditions to ensurethe existence of the stationary optimal policies.
