This package contains all of the python code used for learning. The code is based on Lasagne which is based on Theano.

1. installDependanciesPython3.sh

1. Install Anaconda
2. Follow the setup instruction for Theano which are

	conda install numpy scipy mkl-service libpython m2w64-toolchain <nose> <nose-parameterized> <sphinx> <pydot-ng>

1. sudo apt-get install nvidia-cuda-toolkit nvidia-cuda-dev nvidia-modprobe
   These libraries are needed to compile code for the GPU as well as to check what GPU devices are available

NOTE: Ran into this issue on Ubuntu 16.04 (Theano/Theano#4425) As a temporary workaround, I use the following hack:

Add cmd.append('-D_FORCE_INLINES') just before p = subprocess.Popen( in the file nvcc_compiler.py

python3 trainModel.py --config=settings/particleSim/PPO/PPO.json

These simulations are designed to sample a few simulations in order to get a more reasonable average of the performance of a method.

python3 tuneHyperParameters.py --config=tests/settings/particleSim/PPO/PPO_KERAS_Tensorflow.json --metaConfig=settings/hyperParamTuning/elementAI.json --meta_sim_samples=5 --meta_sim_threads=5 --tuning_threads=2

1. https://github.com/Newmu/Theano-Tutorials
2. https://github.com/spragunr/deep_q_rl