DocumentCode :
2411113
Title :
Convex stochastic control problems
Author :
Fernández-Gaucherand, Emmanuel ; Arapostathis, Aristotle ; Marcus, Steven I.
Author_Institution :
Syst. & Ind. Eng., Arizona Univ., Tucson, AZ, USA
fYear :
1992
fDate :
1992
Firstpage :
2179
Abstract :
The solution of the infinite horizon stochastic control problem under certain criteria, the functional characterization and computation of optimal values and policies, is related to two dynamic programming-like functional equations: the discounted cost optimality equation (DCOE) and the average cost optimality equation (ACOE). The authors consider what useful properties, shared by large and important problem classes, can be used to show that an ACOE holds, and how these properties can be exploited to aid in the development of tractable algorithmic solutions. They address this issue by concentrating on structured solutions to stochastic control models. By a structured solution is meant a model for which value functions and/or optimal policies have some special dependence on the (initial) state. The focus is on convexity properties of the value function
Keywords :
dynamic programming; stochastic systems; average cost optimality equation; convex control; discounted cost optimality equation; dynamic programming-like functional equations; functional characterization; infinite horizon stochastic control problem; optimal values; stochastic control models; Control systems; Cost function; Equations; Industrial engineering; Infinite horizon; Markov processes; Optimal control; Process control; State-space methods; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
Type :
conf
DOI :
10.1109/CDC.1992.371410
Filename :
371410
Link To Document :
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