Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality introduction and summary

Name: Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality introduction and summary
Author: Saldı, Naci, Linder, T., Yüksel, S.

Title	Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality introduction and summary
Author	Saldı, Naci, Linder, T., Yüksel, S.
Publication Date:	2018
Publication Place	- Birkhäuser Basel
Type	Book
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	2324-9749, 978-3-319-79032-9
Record ID	1cbcbb00-14eb-4ea7-b050-08a9bc273e0f
Library Location	Natural and Mathematical Sciences
Date	2018
Sample Text	Control and optimization of dynamical systems in the presence of stochastic uncertainty is a mature field with a large range of applications. A comprehensive treatment of such problems can be found in excellent books and other resources including [7, 16, 29, 68, 84, 95, 104], and [6]. To date, there exist a nearly complete theory regarding the existence and structure of optimal solutions under various formulations as well as computational methods to obtain such optimal solutions for problems with finite state and control spaces. However, there still exist substantial computational challenges involving problems with large state and action spaces, such as standard Borel spaces. For such state and action spaces, obtaining optimal policies is in general computationally infeasible.
DOI	10.1007/978-3-319-79033-6_1

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Özyeğin University

Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality introduction and summary

Author Saldı, Naci, Linder, T., Yüksel, S.

Publication Date 2018

Publication Place - Birkhäuser Basel

Type Book

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 2324-9749, 978-3-319-79032-9

Record ID 1cbcbb00-14eb-4ea7-b050-08a9bc273e0f

Library Location Natural and Mathematical Sciences

Date 2018

Sample Text Control and optimization of dynamical systems in the presence of stochastic uncertainty is a mature field with a large range of applications. A comprehensive treatment of such problems can be found in excellent books and other resources including [7, 16, 29, 68, 84, 95, 104], and [6]. To date, there exist a nearly complete theory regarding the existence and structure of optimal solutions under various formulations as well as computational methods to obtain such optimal solutions for problems with finite state and control spaces. However, there still exist substantial computational challenges involving problems with large state and action spaces, such as standard Borel spaces. For such state and action spaces, obtaining optimal policies is in general computationally infeasible.

DOI 10.1007/978-3-319-79033-6_1