To run the code, first choose the algorithm you want.
Open the algorithm and choose the learn_nnet method to optimize the neural net
To optimize the optimization problems, create a new instance of the one you want
and pass that along with the corresponding fitness function as parameters to the
learn_optimization problem method

GeneticAlgorithmOptimizer is unique in that you must use special fitness functions
(fitness_fourpeaks_ga as opposed to fitness_fourpeaks as it is in the others)

If learning kColors, be sure to set the optimizer's minimize attribute
when it is constructed in learn_optimization problem

Implemented using Python 3.4.3
Packages Used:
--Install all using pip3 for best results--
numpy
scipy
scikit-learn
PyBrain
MatPlotLib
NetworkX

SciPy Install Instructions
--------------------------
sudo apt-get install gfortran
sudo apt-get install libblas-dev liblapack-dev
sudo pip3 install scipy

PyBrain Install Instructions
----------------------------
sudo pip3 install --upgrade git+https://github.com/pybrain/pybrain.git

MatPlotLib Install Instructions
-------------------------------
sudo apt-get install libpng-dev
sudo apt-get install libfreetype6-dev libxft-dev
sudo pip3 install matplotlib

All pip3 commands should be replaced with pip if pip installs to your Python 3.4 directory.
In this case, pip3 installed to Python 3.4 and pip would install to Python 2.7