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Semi-Markov Decision Processes

Probability in the Engineering and Informational Sciences, 2007
Considered are semi-Markov decision processes (SMDPs) with finite state and action spaces. We study two criteria: the expected average reward per unit time subject to a sample path constraint on the average cost per unit time and the expected time-average variability.
M. Baykal-Gürsoy, K. Gürsoy
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On Average Reward Semi-Markov Decision Processes with a General Multichain Structure

Mathematics of Operations Research, 2004
In this paper we investigate average reward semi-Markov decision processes with a general multichain structure using a data-transformation method. By solving the transformed discrete-time average Markov decision processes, we can obtain significant and interesting information on the original average semi-Markov decision processes. If the original semi-
Jianyong Liu, Xiaobo Zhao
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Denumerable Undiscounted Semi-Markov Decision Processes with Unbounded Rewards

Mathematics of Operations Research, 1983
This paper establishes the existence of a solution to the optimality equations in undis-counted semi-Markov decision models with countable state space, under conditions generalizing the hitherto obtained results. In particular, we merely require the existence of a finite set of states in which every pair of states can reach each other via some ...
P J Schweitzer, A Federgruen, H C Tijms
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Semi-Markov Decision Processes with Unbounded Rewards

Management Science, 1973
We consider a semi-Markov decision process with arbitrary action space; the state space is the nonnegative integers. As in queueing systems, we assume that {0, 1, 2, …, n + N} is the set of states accessible from state n in one transition, where N is finite and independent of n.
Steven A. Lippman
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Semi-Markov decision processes

2015
Franciszek Grabski
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Risk-aware semi-Markov decision processes

2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017
In this work we construct a basic theory of risk-aware continuous-time Markov decision processes, and even more broadly, that of semi-Markov decision processes. Methods that account for the preferences of risk-aware agents have been introduced and studied in the context of discrete time problems, however, there has been virtually no such development ...
Jukka Isohataia, William B. Haskell 0001
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Policy Gradient Semi-markov Decision Process

2008 20th IEEE International Conference on Tools with Artificial Intelligence, 2008
This paper proposes a simulation-based algorithm for optimizing the average reward in a parameterized continuous-time, finite-state semi-Markov decision process (SMDP). Our contributions are twofold: First, we compute the approximate gradient of the average reward with respect to the parameters in SMDP controlled by parameterized stochastic policies ...
Ngo, Vien, Chung, TaeChoong
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Cost Rate Heuristics for Semi-Markov Decision Processes [PDF]

, 1991
National Research ...
Glazebrook, K.D., Bailey, Michael P., Whitaker, Lyn R.   +2 more
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Optimal replacement of a system according toa semi-Markov decision process in a semi-Markov environment

Optimization Methods and Software, 2003
This paper investigates an optimal replacement problem of a system in a semi-Markov environment. The system itself deteriorates according to a semi-Markov process, and is further influenced by its environment, which changes according to a semi-Markov process.
Qiying Hu, Wuyi Yue
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