Adaptive control of stochastic systems with unknown disturbance distribution: discounted criteria

Nadine Hilgert () and J. Minjárez-Sosa ()

Mathematical Methods of Operations Research, 2006, vol. 63, issue 3, 443-460

Abstract: We consider a class of discrete-time stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to the equation x t +1 =F(x t , a t , ξ t ), t=0, 1, ..., where the ξ t are i.i.d. random vectors whose common distribution is unknown. Assuming observability of {ξ t }, we use the empirical estimator of its distribution to construct adaptive policies which are asymptotically discounted cost optimal . Copyright Springer-Verlag Berlin Heidelberg 2006

Keywords: Empirical distribution; Discrete-time stochastic systems; Discounted cost criteria; Optimal adaptive policy (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1007/s00186-005-0024-6

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