Results 41 to 50 of about 7,880,220 (196)
Multi-model Markov decision processes
IISE Transactions, 2021 Markov decision processes (MDPs) have found success in many application areas that involve sequential decision making under uncertainty, including the evaluation and design of treatment and screening protocols for medical decision making. However, the data used to parameterize the model can influence what policies are recommended, and multiple ...
Lauren N. Steimle +2 more
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Stochastic monotonicity and duality for one-dimensional Markov processes [PDF]
, 2011 The theory of monotonicity and duality is developed for general one-dimensional Feller processes, extending the approach from [11]. Moreover it is shown that local monotonicity conditions (conditions on the Lévy kernel) are sufficient to prove the well-
Kolokoltsov, V. N. (Vasiliĭ Nikitich)
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Risk probability optimization problem for finite horizon continuous time Markov decision processes with loss rate [PDF]
, 2021 summary:This paper presents a study the risk probability optimality for finite horizon continuous-time Markov decision process with loss rate and unbounded transition rates.
Wen, Xian, Huo, Haifeng
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Unifying Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes [PDF]
Logical Methods in Computer Science, 2017 We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There exist two different views: (i) the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii) the ...
Krishnendu Chatterjee +2 more
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Probabilistic opacity for Markov decision processes [PDF]
Information Processing Letters, 2015 Opacity is a generic security property, that has been defined on (non probabilistic) transition systems and later on Markov chains with labels. For a secret predicate, given as a subset of runs, and a function describing the view of an external observer, the value of interest for opacity is a measure of the set of runs disclosing the secret.
Béatrice Bérard +2 more
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Modelling the profitability of credit cards by Markov decision processes
, 2009 This paper derives a model for the profitability of credit cards, which allow lenders to find the optimal dynamic credit limit policy. The model is a Markov decision process, where the states of the system are based on the borrower's behavioural score ...
Thomas, Lyn C., So, Mee Chi
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Markov decision processes in minimization of expected costs
Croatian Operational Research Review, 2014 Basics of Markov decision processes will be introduced in order to obtain the optimization goal function for minimizing the long-run expected cost. We focus on mini-mization of such cost of the farmer's policy consisting of different decisions in speci c
Marija Rukav +3 more
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Nonlinear Markov semigroups and interacting Lévy type processes [PDF]
, 2007 Semigroups of positivity preserving linear operators on measures of a measurable space X describe the evolutions of probability distributions of Markov processes on X.
Kolokoltsov, V. N. (Vasiliĭ Nikitich)
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Symblicit algorithms for optimal strategy synthesis in monotonic Markov decision processes [PDF]
Electronic Proceedings in Theoretical Computer Science, 2014 When treating Markov decision processes (MDPs) with large state spaces, using explicit representations quickly becomes unfeasible. Lately, Wimmer et al. have proposed a so-called symblicit algorithm for the synthesis of optimal strategies in MDPs, in the
Aaron Bohy +2 more
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Rank-driven Markov processes [PDF]
, 2012 We study a class of Markovian systems of N elements taking values in [0,1] that evolve in discrete time t via randomized replacement rules based on the ranks of the elements.
Grinfeld, Michael +2 more
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