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This article considers the average optimality for a continuous-time Markov decision process with Borel state and action spaces and an arbitrarily unbounded nonnegative cost rate. The existence of a deterministic stationary optimal policy is…

Optimization and Control · Mathematics 2014-03-05 Yi Zhang

We consider discrete-time Markov Decision Processes with Borel state and action spaces and universally measurable policies. For several long-run average cost criteria, we establish the following optimality results: the optimal average cost…

Optimization and Control · Mathematics 2021-04-02 Huizhen Yu

This paper presents a new condition for the existence of optimal stationary policies in average-cost continuous-time Markov decision processes with unbounded cost and transition rates, arising from controlled queueing systems. This…

Optimization and Control · Mathematics 2015-04-23 Cao Ping , Xie Jingui

We consider average-cost Markov decision processes (MDPs) with Borel state spaces, countable, discrete action spaces, and strictly unbounded one-stage costs. For the minimum pair approach, we introduce a new majorization condition on the…

Optimization and Control · Mathematics 2020-05-06 Huizhen Yu

This paper studies discrete-time average-cost infinite-horizon Markov decision processes (MDPs) with Borel state and action sets. It introduces new sufficient conditions for { the} validity of optimality inequalities and optimality…

Optimization and Control · Mathematics 2025-01-28 Eugene A. Feinberg , Pavlo O. Kasyanov , Liliia S. Paliichuk

This paper describes sufficient conditions for the existence of optimal policies for Partially Observable Markov Decision Processes (POMDPs) with Borel state, observation, and action sets and with the expected total costs. Action sets may…

Optimization and Control · Mathematics 2014-07-02 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

This paper, based on the compactness-continuity and finite value conditions, establishes the sufficiency of the class of stationary policies out of the general class of history-dependent ones for a constrained continuous-time Markov…

Optimization and Control · Mathematics 2014-10-31 Yi Zhang

This paper studies continuous-time Markov decision processes under the risk-sensitive average cost criterion. The state space is a finite set, the action space is a Borel space, the cost and transition rates are bounded, and the…

Optimization and Control · Mathematics 2015-12-22 Qingda Wei , Xian Chen

For a Markov decision process with countably infinite states, the optimal value may not be achievable in the set of stationary policies. In this paper, we study the existence conditions of an optimal stationary policy in a countable-state…

Optimization and Control · Mathematics 2020-07-06 Li Xia , Xianping Guo , Xi-Ren Cao

Calculating optimal policies is known to be computationally difficult for Markov decision processes (MDPs) with Borel state and action spaces. This paper studies finite-state approximations of discrete time Markov decision processes with…

Optimization and Control · Mathematics 2016-09-23 Naci Saldi , Serdar Yüksel , Tamás Linder

This note describes sufficient conditions under which total-cost and average-cost Markov decision processes (MDPs) with general state and action spaces, and with weakly continuous transition probabilities, can be reduced to discounted MDPs.…

Optimization and Control · Mathematics 2017-11-21 Eugene A. Feinberg , Jefferson Huang

As is well known, average-cost optimality inequalities imply the existence of stationary optimal policies for Markov Decision Processes with average costs per unit time, and these inequalities hold under broad natural conditions. This paper…

Optimization and Control · Mathematics 2016-10-04 Eugene A. Feinberg , Yan Liang

We consider average-cost Markov decision processes (MDPs) with Borel state and action spaces and universally measurable policies. For the nonnegative cost model and an unbounded cost model, we introduce a set of conditions under which we…

Optimization and Control · Mathematics 2019-01-14 Huizhen Yu

This paper deals with unconstrained discounted continuous-time Markov decision processes in Borel state and action spaces. Under some conditions imposed on the primitives, allowing unbounded transition rates and unbounded (from both above…

Optimization and Control · Mathematics 2011-03-02 Alexey Piunovskiy , Yi Zhang

This paper provides conditions under which total-cost and average-cost Markov decision processes (MDPs) can be reduced to discounted ones. Results are given for transient total-cost MDPs with tran- sition rates whose values may be greater…

Optimization and Control · Mathematics 2017-05-04 Eugene A. Feinberg , Jefferson Huang

We study discrete-time discounted constrained Markov decision processes (CMDPs) on Borel spaces with unbounded reward functions. In our approach the transition probability functions are weakly or set-wise continuous. The reward functions…

Optimization and Control · Mathematics 2019-03-29 Eugene A. Feinberg , Anna Jaśkiewicz , Andrzej S. Nowak

We consider a piecewise deterministic Markov decision process, where the expected exponential utility of total (nonnegative) cost is to be minimized. The cost rate, transition rate and post-jump distributions are under control. The state…

Optimization and Control · Mathematics 2017-11-22 Xin Guo , Yi Zhang

We consider average-cost Markov decision processes (MDPs) with Borel state and action spaces and universally measurable policies. For the nonnegative cost model and an unbounded cost model with a Lyapunov-type stability character, we…

Optimization and Control · Mathematics 2020-12-17 Huizhen Yu

This paper presents an axiomatic approach to finite Markov decision processes where the discount rate is zero. One of the principal difficulties in the no discounting case is that, even if attention is restricted to stationary policies, a…

Optimization and Control · Mathematics 2022-11-23 Adam Jonsson

This paper studies convergence properties of optimal values and actions for discounted and average-cost Markov Decision Processes (MDPs) with weakly continuous transition probabilities and applies these properties to the stochastic…

Optimization and Control · Mathematics 2017-03-21 Eugene A. Feinberg , Mark E. Lewis
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