NDLI: Two time-scale stochastic approximation for constrained stochastic optimization and constrained Markov decision problems

Content Provider	IEEE Xplore Digital Library
Author	Tadic, V.B. Doucet, A. Singh, S.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia (Tadic, V.B.)
Abstract	In this paper, constrained stochastic optimization problems are considered for the case where the constraint functions are convex (but the criterion function can be non-convex) and the criterion and constraint functions are available only through their noisy observations. A general algorithm of the two time-scale stochastic approximation type is proposed for these problems. The proposed algorithm is applied to Markov decision problems with average cost, average constraints and parameterized stationary policy. The asymptotic behavior of the proposed algorithm is analyzed for the case where the algorithm step-sizes are constant and the noise in the observations of the criterion and constraint functions depends on the algorithm iterates.
Sponsorship	American Automatic Control Council IFAC
Starting Page	4736
Ending Page	4741
File Size	398603
Page Count	6
File Format	PDF
ISBN	0780378962
ISSN	07431619
DOI	10.1109/ACC.2003.1242471
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Constraint optimization Convergence Constraint theory Lagrangian functions Approximation algorithms Stochastic resonance Costs Postal services Optimization methods
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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