4 results for Azzato, Jeffrey D

SOCSol4L: an Improved MATLAB (R) Package For Approximating the Solution to a ContinuousTime Stochastic Optimal Control Problem
Azzato, Jeffrey D; Krawczyk, Jacek B (2006)
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Victoria University of WellingtonComputing the solution to a stochastic optimal control problem is difficult. A method of approximating a solution to a given continuoustime stochastic optimal control problem using Markov chains was developed in [Kra01]. This paper describes a suite of MATLAB (R) routines implementing this method.
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A Report on NISOCSol: an Algorithm For Approximating Markovian Equlibria in Dynamic Games with CoupledConstraints
Krawczyk, Jacek B; Azzato, Jeffrey D (2006)
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Victoria University of WellingtonIn this report, we outline a method for approximating a Markovian (or feedbackNash) equilibrium of a dynamic game, possibly subject to coupledconstraints. We treat such a game as a "multiple" optimal control problem. A method for approximating a solution to a given optimal control problem via backward induction on Markov chains was developed in [Kra01]. A Markovian equilibrium may be obtained numerically by adapting this backward induction approach to a stage NikaidoIsoda function (described in [KZ06]).
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Parallel SOCSol: a Parallel MATLAB (R) Package For Approximating the Solution to a ContinuousTime Stochastic Optimal Control Problem
Azzato, Jeffrey D; Krawczyk, Jacek B (2008)
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Victoria University of WellingtonThis article is a modified version of [AK06]. Both articles explain how a suite of MATLAB (R) routines distributed under the generic name SOCSol can be used to obtain optimal solutions to continuoustime stochastic optimal control problems. The difference between the SOCSol suites described by the articles arises from the underlying computing platforms used. This article describes a beta version of SOCSol that utilises the MATLAB (R) Parallel Computing Toolbox (TM), while [AK06] describes a version of SOCSol that does not use parallel computing methods.
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A Report on Using Parallel MATLAB (R) For Solutions to Stochastic Optimal Control Problems
Azzato, Jeffrey D; Krawczyk, Jacek B (2008)
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Victoria University of WellingtonParallel MATLAB (R) is a recent MathWorks (TM) product enabling the use of parallel computing methods on multicore personal computers. SOCSol is the generic name of a suite of MATLAB (R) routines that can be used to obtain optimal solutions to continuoustime stochastic optimal control problems. In this report, we compare the performance of a new version of SOCSol utilising parallel MATLAB (R) with that of another version not using parallel computing methods.
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