gaunt / bellman Goto Github PK

Code for solving dynamic programming optimization problems (i.e. Bellman equations)
through value & policy function iteration.  This code was developed as part of my
paper, "Maturity Mismatch and Fractional-Reserve Banking" (see http://rncarpio.com for more
on my economics research).

Some projects that the code relies upon are:
 - Python, Scipy, Numpy : http://python.org, http://scipy.org
 - PythonXY, a convenient all-in-one distribution for Python : http://pythonxy.com
 - Intel's Thread Building Blocks library for parallel computing : http://threadingbuildingblocks.org
 - Boost.Python, for mixing C++ with Python : http://www.boost.org/doc/libs/release/libs/python/
 - PyUBlas, a glue layer between numpy and C++ matrices : http://mathema.tician.de/software/pyublas

I compiled and ran on Windows 7, Visual Studio 10.  Other platforms should work, but I haven't tested
them.