DocumentCode
321198
Title
Linear programming approximations for Markov control processes in metric spaces
Author
Hernandez-Lerma, O. ; Lasserre, Jean B.
Author_Institution
CINVESTAV-IPN, Mexico City, Mexico
Volume
3
fYear
1997
fDate
10-12 Dec 1997
Firstpage
2291
Abstract
This paper presents LP approximations for Markov control processes in metric spaces. The approximations are based on aggregation and relaxation of constraints, as well as inner approximations of the decision variables. In particular, conditions are given under which the control problem´s optimal value is approximated by a sequence of finite-dimensional LP
Keywords
Markov processes; approximation theory; linear programming; optimal control; stochastic systems; LP approximations; Markov control processes; constraint aggregation; constraint relaxation; finite-dimensional LP sequence; inner approximations; linear programming approximations; metric spaces; optimal control; Convergence; Costs; Extraterrestrial measurements; Level set; Linear approximation; Linear programming; Optimal control; Process control; State-space methods; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location
San Diego, CA
ISSN
0191-2216
Print_ISBN
0-7803-4187-2
Type
conf
DOI
10.1109/CDC.1997.657116
Filename
657116
Link To Document