Approximation, estimation and control of stochastic systems under a randomized discounted cost criterion

Title:

Approximation, estimation and control of stochastic systems under a randomized discounted cost criterion

Creator:

Gonzáles-Hernández, Juan, López-Martínez, Raquiel R., and Minjárez-Sosa, J. Adolfo

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:910b54cf-e8a2-4ce0-8bd4-1263b5cab4ea
uuid:910b54cf-e8a2-4ce0-8bd4-1263b5cab4ea

Subject:

discounted cost, random rate, stochastic system, approximation algorithms, and density estimation

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The paper deals with a class of discrete-time stochastic control processes under a discounted optimality criterion with random discount rate, and possibly unbounded costs. The state process { x_{t} } and the discount process { \alpha_{t} } evolve according to the coupled difference equations x_{t+1}=F(x_{t},\alpha _{t},a_{t},\xi _{t}), \alpha_{t+1}=G(\alpha _{t},\eta _{t}) where the state and discount disturbance processes { \xi _{t} } and { \eta _{t} } are sequences of i.i.d. random variables with densities \rho^{\xi } and \rho^{\eta } respectively. The main objective is to introduce approximation algorithms of the optimal cost function that lead up to construction of optimal or nearly optimal policies in the cases when the densities \rho ^{\xi } and \rho ^{\eta } are either known or unknown. In the latter case, we combine suitable estimation methods with control procedures to construct an asymptotically discounted optimal policy.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[737]-754

Source:

Kybernetika | 2009 Volume:45 | Number:5

Harvested from:

CDK

Metadata only:

false