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may be quite complicated in the sense that the prescribed actions may depend on the whole history of the system An important class of policies is the subclass of stationary policies A stationary policy R is a policy that assigns to each state i a xed action a = Ri and always uses this action whenever the system is in state i For example, in the maintenance problem with N = 5, the policy R prescribing a preventive repair only in the states 3 and 4 is given by R1 = 0, R2 = 0, R3 = R4 = 1 and R5 = R6 = 2 For n = 0, 1, , de ne Xn = the state of the system at the nth decision epoch Under a given stationary policy R, we have P {Xn+1 = j | Xn = i} = pij (Ri ), regardless of the past history of the system up to time n Hence under a given stationary policy R the stochastic process {Xn } is a discrete-time Markov chain with one-step transition probabilities pij (Ri ) This Markov chain incurs a cost ci (Ri ) each time the system visits state i Thus we can invoke results from Markov chain theory to specify the long-run average cost per time unit under a given stationary policy In view of the Markov assumption made and the fact that the planning horizon is in nitely long, it will be intuitively clear that it is suf cient to consider only the class of stationary policies However, other policies are conceivable: policies whose actions depend on the past states or policies whose actions are determined by a random mechanism This issue raises a fundamental question in Markov decision theory: does there exist an optimal policy among the class of all conceivable policies and, if an optimal policy exists, is such a policy a stationary policy The answer to these questions is yes for the average-cost Markov decision model with a nite state space and nite action sets However, a mathematical proof requires rather deep arguments The interested reader is referred to Derman (1970) and Puterman (1994) for a proof From these books the reader will learn that the issue of the existence of an optimal (stationary) policy is a very subtle one Especially for the average cost criterion, the optimality questions become very complicated when the state space is not nite but countably in nite Even in simple countable-state models, average cost optimal policies need not exist and, when they do, they need not be stationary; see Puterman (1994) In the average-cost Markov decision model with a nite state space and nite action sets these dif culties do not arise and the analysis can be restricted to the class of stationary policies. asp.net c# read pdf file Read and Extract PDF Text from C# / VB. NET applications - GemBox
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download pdf in mvc HI, We have an application which Gets a Scanned paper PDF files, Our ... / read - image-text-from- pdf -file-to-itextsharp-in- aspnet -c. aspx . 0 ... asp.net core pdf editor In this section we will establish a key result that underlies the various algorithms for the computation of an average cost optimal policy Before doing this, we discuss the long-run average cost per time unit for a stationary policy Average cost for a given stationary policy Fix a stationary policy R Under policy R each time the action a = Ri is taken whenever the system is in state i at a decision epoch The process {Xn } describing the state of the system at the decision epochs is a Markov chain with one-step transition probabilities pij (Ri ), i, j I when policy R is used Denote the n-step transition probabilities of this Markov chain by rdlc upc-a, c# generate upc barcode, java upc-a reader, crystal reports code 128 ufl, upc connect box nincs internet, asp.net pdf 417 reader read pdf in asp.net c# Read a PDF file using C# .Net | The ASP . NET Forums
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