Discounted dynamic programming on Euclidean spaces
A. Nowak (1979)
Applicationes Mathematicae
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Displaying similar documents to “Uniform value in dynamic programming”
Discounted dynamic programming on Euclidean spaces
Dynamic Programming and Markov Processes - Howard, Ronald A.
H.P. Künzi (1962)
Metrika
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Contents of volume 35 issue 3
(2006)
Control and Cybernetics
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Stochastic dynamic programming with random disturbances
Regina Hildenbrandt (2003)
Discussiones Mathematicae Probability and Statistics
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Several peculiarities of stochastic dynamic programming problems where random vectors are observed before the decision ismade at each stage are discussed in the first part of this paper. Surrogate problems are given for such problems with distance properties (for instance, transportation problems) in the second part.
Approximations for Markov decision problems
Gerhard Hübner (1983)
Acta Universitatis Carolinae. Mathematica et Physica
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On a general dynamic programming problem
A. Nowak (1977)
Colloquium Mathematicae
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A complementarity approach for solving Leontief substitution systems and (generalized) Markov decision processes
Gary J. Koehler (1979)
RAIRO - Operations Research - Recherche Opérationnelle
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Risk-sensitive average optimality in Markov decision processes
Karel Sladký (2018)
Kybernetika
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In this note attention is focused on finding policies optimizing risk-sensitive optimality criteria in Markov decision chains. To this end we assume that the total reward generated by the Markov process is evaluated by an exponential utility function with a given risk-sensitive coefficient. The ratio of the first two moments depends on the value of the risk-sensitive coefficient; if the risk-sensitive coefficient is equal to zero we speak on risk-neutral models. Observe that the first...
How to treat decision problems by different programming methodologies
G. Cioni, A. Miola (1988)
Banach Center Publications
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Second Order optimality in Markov decision chains
Karel Sladký (2017)
Kybernetika
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The article is devoted to Markov reward chains in discrete-time setting with finite state spaces. Unfortunately, the usual optimization criteria examined in the literature on Markov decision chains, such as a total discounted, total reward up to reaching some specific state (called the first passage models) or mean (average) reward optimality, may be quite insufficient to characterize the problem from the point of a decision maker. To this end it seems that it may be preferable if not...
Interactive compromise hypersphere method and its applications
Sebastian Sitarz (2012)
RAIRO - Operations Research - Recherche Opérationnelle
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The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of...
Interactive compromise hypersphere method and its applications
Sebastian Sitarz (2012)
RAIRO - Operations Research
Similarity:
The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of...