Hybrid Methods for Continuous Space Dynamic Programming
We propose a method for solving continuous-state and action-stochastic dynamic programs that is a hybrid between the continuous space projection methods introduced by Judd and the discrete space methods introduced by Bellman. Our hybrid approach yields a smooth representation of the value function while preserving the computational simplicity of discrete dynamic programming. Our method is especially well suited for implementation in a vector processing environment such as MATLAB or GAUSS, and makes it possible to automate the setup and solution of continuous space dynamic programs in a way that previously seemed elusive.
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|Date of creation:||01 Mar 1999|
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Web page: http://fmwww.bc.edu/CEF99/
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