Advanced Search
MyIDEAS: Login to save this paper or follow this series

SOCSol4L An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem

Contents:

Author Info

  • Azzato, Jeffrey
  • Krawczyk, Jacek

Abstract

Computing the solution to a stochastic optimal control problem is difficult. A method of approximating a solution to a given stochastic optimal control problem using Markov chains was developed in [1]. This paper describes a suite of MATLAB functions implementing this method of approximating a solution to a given continuous stochastic optimal control problem.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://mpra.ub.uni-muenchen.de/1179/
File Function: original version
Download Restriction: no

File URL: http://mpra.ub.uni-muenchen.de/8946/
File Function: revised version
Download Restriction: no

File URL: http://mpra.ub.uni-muenchen.de/10015/
File Function: revised version
Download Restriction: no

Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1179.

as in new window
Length:
Date of creation: 2006
Date of revision:
Handle: RePEc:pra:mprapa:1179

Contact details of provider:
Postal: Schackstr. 4, D-80539 Munich, Germany
Phone: +49-(0)89-2180-2219
Fax: +49-(0)89-2180-3900
Web page: http://mpra.ub.uni-muenchen.de
More information through EDIRC

Related research

Keywords: Computational techniques; Economic software; Computational methods in stochastic optimal control; Computational economics; Approximating Markov decision chains;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Jacek B. Krawczyk & Alistair Windsor, 1997. "An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains," Computational Economics, EconWPA 9710001, EconWPA.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Foster, Jarred & Krawczyk, Jacek B, 2013. "Sensitivity of cautious-relaxed investment policies to target variation," Working Paper Series, Victoria University of Wellington, School of Economics and Finance 2972, Victoria University of Wellington, School of Economics and Finance.
  2. Krawczyk, Jacek & Azzato, Jeffrey, 2006. "NISOCSol an algorithm for approximating Markovian equilibria in dynamic games with coupled-constraints," MPRA Paper 1195, University Library of Munich, Germany.
  3. Foster, Jarred, 2011. "Target variation in a loss avoiding pension fund problem," MPRA Paper 36177, University Library of Munich, Germany.
  4. Azzato, Jeffrey D. & Krawczyk, Jacek, 2007. "Using a finite horizon numerical optimisation method for a periodic optimal control problem," MPRA Paper 2298, University Library of Munich, Germany.
  5. Krawczyk, Jacek B & Pharo, Alastair S, 2014. "InfsocSol3: An updated MATLABĀ® package for approximating the solution to a continuous-time infinite horizon stochastic optimal control problem," Working Paper Series, Victoria University of Wellington, School of Economics and Finance 3412, Victoria University of Wellington, School of Economics and Finance.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:1179. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.