Titlebook: Stochastic Systems: Modeling, Identification and Optimization II; Roger J.- B. Wets Book 1976Latest edition Springer-Verlag Berlin Heidelb

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书目名称Stochastic Systems: Modeling, Identification and Optimization II影响因子(影响力)




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书目名称Stochastic Systems: Modeling, Identification and Optimization II网络公开度学科排名




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书目名称Stochastic Systems: Modeling, Identification and Optimization II被引频次学科排名




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书目名称Stochastic Systems: Modeling, Identification and Optimization II读者反馈学科排名

insolence

Nonanticipativity and ,,-martingales in stochastic optimization problems,on and is shown to be related to the more familiar concept—in stochastic programming—of relatively complete recourse. It is also shown that this restriction renders possible the justification of the dynamic programming technique.

特征

Monotone optimal policies for Markov decision processes,s for monotone transition probabilities. These play an important role in establishing the existence of monotone optimal policies. We illustrate this for controlled random walks and a multi-machine maintenance model.

B-cell

The structure of jump processes and related control problems,cription” of jump times and locations. This formulation enables us to derive in an elementary way the representation of all local martingales on the σ-fields generated by such a process as integrals with respect to a certain fundamental family of martingales. Two applications of this result are stud

忘川河

General necessary conditions for optimal control of stochastic systems, is a Brownian motion. Using Girsanov’s approach to define solutions and Neustadt’s theory of extremals, a maximum principle is derived wherein the adjoint variables are the integrands of the stochastic integrals which represent certain martingales determined by the problem.

漂亮

Regenerative Markov decision models, the existence of stationary optimal policies with respect to discounted expected and average expected return is shown. Also sensitive discount optimal policies do exist and limit decision rules, as the discount-factor tends to one, of discounted optimal rules are bias or equivalently average-overta

Coronary-Spasm

Discrete approximations for stochastic control problems with control acting continuously and impulssly acting control. Various computationally convenient Markov chain approximations to the problems are developed, and it is shown that the costs for the sequence of approximations converge to the optimal cost for original problems.

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Discretizations of multistage stochastic programming problems,he problem can be solved approximately, or in the limit, by solving a sequence of linear programming problems in ... Each of these problems is obtained by approximating the given random vectors by simple random vectors.

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生命层

Nonanticipativity and ,,-martingales in stochastic optimization problems,regularity conditions and a condition of “nonanticipative feasibility”, a system of Lagrange multipliers, characterized by a martingale property, can be associated with the constraints of the problem. Nonanticipative feasibility is expressed in terms of the nonanticipativity of a certain multifuncti