Deterministic optimal policies for Markov control processes with pathwise constraints

• Autorzy: Armando F. Mendoza-Pérez , Onésimo Hernández-Lerma
• Języki publikacji: EN

Abstrakty

EN

This paper deals with discrete-time Markov control processes in Borel spaces with unbounded rewards. Under suitable hypotheses, we show that a randomized stationary policy is optimal for a certain expected constrained problem (ECP) if and only if it is optimal for the corresponding pathwise constrained problem (pathwise CP). Moreover, we show that a certain parametric family of unconstrained optimality equations yields convergence properties that lead to an approximation scheme which allows us to obtain constrained optimal policies as the limit of unconstrained deterministic optimal policies. In addition, we give sufficient conditions for the existence of deterministic policies that solve these constrained problems.

Kategorie tematyczne

• 90C40: Markov and semi-Markov decision processes
• 93E20: Optimal stochastic control

• Wydawca: Institute of Mathematics Polish Academy of Sciences
• Czasopismo: Applicationes Mathematicae
• Rocznik: 2012
• Tom: 39
• Numer: 2
• Strony: 185-209

Daty

wydano

2012

Twórcy

autor

Armando F. Mendoza-Pérez

• CEFyMAP-UNACH, Cuarta Oriente Norte 1428, entre 13 y 14 norte, C.P. 29040, Tuxtla Gutiérrez, Chiapas, México

autor

Onésimo Hernández-Lerma

• Mathematics Department, CINVESTAV-IPN, A. Postal 14-740, México D.F. 07000, México

Identyfikatory

DOI

10.4064/am39-2-6