SOCSol4L An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem
AbstractComputing 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 . This paper describes a suite of MATLAB functions implementing this method of approximating a solution to a given continuous stochastic optimal control problem.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 1179.
Date of creation: 2006
Date of revision:
Computational techniques; Economic software; Computational methods in stochastic optimal control; Computational economics; Approximating Markov decision chains;
Find related papers by JEL classification:
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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- Jacek B. Krawczyk & Alistair Windsor, 1997. "An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains," Computational Economics 9710001, EconWPA.
- 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.
- 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.
- Foster, Jarred, 2011. "Target variation in a loss avoiding pension fund problem," MPRA Paper 36177, University Library of Munich, Germany.
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