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On Average Reward Semi-Markov Decision Processes with a General Multichain Structure
Mathematics of Operations Research, 2004In 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, 1983This 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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Finite horizon semi-Markov decision processes with application to maintenance systems
European Journal of Operational Research, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xianping Guo, Yonghui Huang
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Semi-Markov Decision Processes
Probability in the Engineering and Informational Sciences, 2007Considered 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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Risk-aware semi-Markov decision processes
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017In 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, 2008This 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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Semi-Markov Decision Process With Partial Information for Maintenance Decisions
IEEE Transactions on Reliability, 2014A critical factor that prevents optimal scheduling of maintenance interventions is the uncertainty regarding the current condition of the asset under consideration, as well as the rate at which deterioration takes place. However, current maintenance modeling and optimization techniques assume that the condition of the asset is either known, or assumed ...
Rengarajan Srinivasan +1 more
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Application of Semi-Markov Decision Process in Bridge Management
IABSE Reports, 2015<p>The state-of-the-art Bridge Management Systems (BMSs) feature tightly coupled deterioration and preservation optimization model that enable determining the most cost-effective maintenance strategies at both the project and network levels. In other to improve deterioration model, many authors suggest the application of Weibull distribution for ...
Rade Hajdin +2 more
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