Abstract
A large class of problems in stochastic programming (see [7]), stochastic control (see [1,3]), estimation theory (see [5]) and optimal design of networks (see [6]) can be formulated within the following abstract framework:
Let X be a Banach space, Z a separable Banach space, (Ω,A,P) a probability space with elements ω, T=T(ω) a stochastic, linear operator from X to Z, describing the input-output behaviour x → T(ω)x of some abstract stochastic linear control system and let v=v(ω) be a random variable in Z, playing the role of an abstract stochastic target which must be attained as good as possible by selecting a control variable x.
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Marti, K. (1976). Approximations to Stochastic Optimization Problems. In: Oettli, W., Ritter, K. (eds) Optimization and Operations Research. Lecture Notes in Economics and Mathematical Systems, vol 117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46329-7_18
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DOI: https://doi.org/10.1007/978-3-642-46329-7_18
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