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Batch policy learning in average reward Markov decision processes
Annals of Statistics, 2022Susan A Murphy +2 more
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2012
This paper presents a method of comparing two queueing networks. In this context one typically thinks of one network as being a solvable modification of another unsolvable one of practical interest. The approach is essentially based upon evaluating steady-state performance measures by a cumulative reward structure and strongly relies upon the ...
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This paper presents a method of comparing two queueing networks. In this context one typically thinks of one network as being a solvable modification of another unsolvable one of practical interest. The approach is essentially based upon evaluating steady-state performance measures by a cumulative reward structure and strongly relies upon the ...
openaire +2 more sources
Using a Markov reward model to estimate spend-down costs for a geriatric department
Journal of the Operational Research Society, 1998Sally Mcclean, Peter Millard
exaly
Compositionality for Markov reward chains with fast and silent transitions
Performance Evaluation, 2009Ana Sokolova, E P De Vink
exaly
A Parametric Uncertainty Analysis Method for Markov Reliability and Reward Models
IEEE Transactions on Reliability, 2012Alejandro Dominguez-Garcia +1 more
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Constrained Markov Decision Processes with Expected Total Reward Criteria
SIAM Journal on Control and Optimization, 2019Andrzej Nowak, Anna Jaśkiewicz
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Solving Semi-Markov Decision Problems Using Average Reward Reinforcement Learning
Management Science, 1999Abhijit Gosavi +2 more
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Achieving Target State-Action Frequencies in Multichain Average-Reward Markov Decision Processes
Mathematics of Operations Research, 2002Dmitry Krass, O J Vrieze
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