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An effective gradient projection method for stochastic optimal control

Du, Ning, Shi, Jingtao, Liu, Wenbin (2013) An effective gradient projection method for stochastic optimal control. International Journal of Numerical Analysis and Modeling, 10 (4). pp. 757-774. ISSN 1705-5105. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:40802)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://www.math.ualberta.ca/ijnam/Volume-10-2013/N...

Abstract

In this work, we propose a simple yet effective gradient projection algorithm for a class of stochastic optimal control problems. The basic iteration block is to compute gradient projection of the objective functional by solving the state and co-state equations via some Euler methods and by using the Monte Carlo simulations. Convergence properties are discussed and extensive numerical tests are carried out. Possibility of extending this algorithm to more general stochastic optimal control is also discussed.

Item Type: Article
Uncontrolled keywords: Gradient projection algorithm, Numerical method, Stochastic optimal control
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Tracey Pemble
Date Deposited: 16 Apr 2014 10:18 UTC
Last Modified: 06 May 2020 03:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/40802 (The current URI for this page, for reference purposes)
Liu, Wenbin: https://orcid.org/0000-0001-5966-6235
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