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Coupling based estimation approaches for the average reward performance potential in Markov chains
Automatica, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yanjie Li +4 more
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Recursive Approaches for Single Sample Path Based Markov Reward Processes
Asian Journal of Control, 2001ABSTRACTIn this paper, two single sample path‐based recursive approaches for Markov decision problems are proposed. One is based on the simultaneous perturbation approach and can be applied to the general state problem, but its convergence rate is low.
Hai‐Tao Fang +2 more
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A unified approach for semi-Markov decision processes with discounted and average reward criteria
Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014On the basis of the sensitivity-based optimization, we develop a unified optimization approach for semi-Markov decision processes (SMDPs) with infinite horizon discounted and average reward criteria. We show that the sensitivity formula under average reward criteria is a limitation case of discounted reward criteria.
Yanjie Li, Huijing Wang, Haoyao Chen
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A Symbolic Approach to the Analysis of Multi-Formalism Markov Reward Models
2013When modelling large systems, modularity is an important concept, as it aids modellers to master the complexity of their model. Moreover, employing different modelling formalisms within the same modelling project has the potential to ease the description of various parts or aspects of the overall system.
Kai Lampka, Markus Siegle
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On Markov Reward Approach to Failure Criticality Importance Assessment for Aging Multi-state System
2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO), 2016The paper presents the Markov Reward approach to failure critical importance assessment for the aging multi-state system. Aging is treated as increasing failure rate. Failure criticality importance for multi-state system is directly calculated via calculation of mean number of system failures.
Shay Toledano +4 more
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A unified approach to adaptive control of average reward Markov decision processes
OR Spektrum, 1988The paper presents a general optimization method for adaptive average reward Markov decision problems. Optimal decisions are determined by applying after each observation of the state and estimation of the unknown parameter a policy improvement step to an auxiliary value function, converging with increasing time to the true relative value.
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The Markov Reward Approach for Selecting a Traction Electric Motor Based on Reliability Features
2018This chapter presents the Markov reward approach to the comparative analysis of different types of traction electric motors for hybrid-electric propulsion systems, that is, multi-state systems (MSSs), for icebreaker ships operating in Arctic waters. The preliminary results show that there are several appropriate machine types and that it is therefore ...
Igor Bolvashenkov +4 more
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2019
This paper discusses a unified approach to reliability, availability and performabilityanalysis of complex engineering systems. Theoretical basis of this approach is continuous-timediscrete state Markov processes with rewards. From reliability modeling point of view complexsystems are the systems with static and dynamic redundancy, imperfect fault ...
Vikotora, V. +2 more
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This paper discusses a unified approach to reliability, availability and performabilityanalysis of complex engineering systems. Theoretical basis of this approach is continuous-timediscrete state Markov processes with rewards. From reliability modeling point of view complexsystems are the systems with static and dynamic redundancy, imperfect fault ...
Vikotora, V. +2 more
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Error Bounds and Comparison Results: The Markov Reward Approach For Queueing Networks
2010This chapter presents an approach to compare two Queueing Networks. Here one may typically think of one network to be a solvable modification of another unsolvable one of practical interest.
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A symbolic approach to the state graph based analysis of high-level Markov reward models.
2007Markov reward models considered in this thesis are compactly described by means of Markovian extensions of well-known high-level model description formalisms. For numerically computing performance and dependability (= performability) measures of high-level system models, the latter must be transformed into low-level representations, where the ...
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