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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, 2014
On 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
openaire   +1 more source

Constrained semi-Markov decision processes with ratio and time expected average criteria in Polish spaces

Optimization, 2013
This paper deals with the ratio and time expected average criteria for constrained semi-Markov decision processes (SMDPs). The state and action spaces are Polish spaces, the rewards and costs are unbounded from above and from below, and the mean holding times are allowed to be unbounded from above. First, under general conditions we prove the existence
Qingda Wei, Xianping Guo
openaire   +1 more source

Criteria for selecting the relaxation factor of the value iteration algorithm for undiscounted Markov and semi-Markov decision processes

Operations Research Letters, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Herzberg, Meir, Yechiali, Uri
openaire   +2 more sources

An Optimal Reprofiling Policy for High-Speed Train Wheels Subject to Wear and External Shocks Using a Semi-Markov Decision Process

IEEE Transactions on Reliability, 2018
Wheels are one of the three components of rail vehicles that are most affected by wear, having significant implications on safety and comfort. For the safety of vehicles, maintenance activities are needed for worn wheels to ensure their normal geometry, where reprofiling plays the most important role in maintenance.
E. Mingcheng   +3 more
openaire   +1 more source

Markovian Decision Processes (Semi-Markov and Markov) with Complete Information (Completely Observable)

1990
In Figure 4.1(a) a diagrammatic representation of a semi-Markov decision process is presented; special attention to transition probabilities \( \left[ {\mathop p\nolimits_{ij,}^k } \right]\) and waiting time probabilities \( \mathop h\nolimits_{ij(m)}^k \) is given.
openaire   +1 more source

VMDP-program for solving optimality problems in vector criterion Markov and semi-Markov decision processes

Optimization, 1991
Optimality problems in infinite horizon discrete time vector criterion Markov and semi-Markov decision processes can be expressed as standard problems of multiple objective linear programming. “VMDP” is a FORTRAN program for enumerating the objective function coefficients and constraint coefficients in these problems and finding all nondominated ...
openaire   +1 more source

Delay time-based inspection and replacement optimization under Semi-Markov decision process

2022 Global Reliability and Prognostics and Health Management (PHM-Yantai), 2022
Li Yang   +4 more
openaire   +1 more source

Real-Time Scalable Task Offloading in Edge Computing Using Semi-Markov Decision Processes and Attention-Based Deep Reinforcement Learning

Journal of Optimization in Soft Computing,2(4 ...
Mirzaei, Abbas   +7 more
openaire   +1 more source

A Theory for Semi-Markov Decision Processes with Unbounded Costs and Its Application to the Optimal Control of Queueing Systems

1976
Abstract : Semi-Markov decision processes with countable state and action spaces are investigated. The optimality criteria considered are the average cost criterion, the undiscounted cost criterion, and the discounted cost criterion. The common assumption of bounded costs has been replaced by some considerably weaker conditions.
openaire   +1 more source

Molecular imaging in oncology: Current impact and future directions

Ca-A Cancer Journal for Clinicians, 2022
Steven P Rowe, Martin G Pomper
exaly  

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