Deep Policy Gradient Reinforcement Learning

This repository has the code from my O'Reilly article 'Reinforcement Learning w/ TensorFlow' published on.

This code contains tools for implementing the reinforcement learning algorthing REINFORCE w/ baselines using TensorFlow and a convolutional Neural Network

Required Packages

• TensorFlow v1.4
• Jupyter
• NumPy
• Scipy
• Skimage
• Matplotlib
• VizDoom

There are two ways you can install these packages: by using Docker or by using native Python 3.5. If you use Docker you will not be able to render the environment.

Using Docker

1. Download and install Docker. If using Ubuntu 14.04/16.04 I wrote my own instructions for installing docker here.

2. Download and unzip this entire repo from GitHub, either interactively, or by entering

   git clone https://github.com/wagonhelm/Deep-Policy-Gradient.git
   

3. Open your terminal and use cd to navigate into the directory of the repo on your machine

   cd Deep-Policy-Gradient
   

4. To build the Dockerfile, enter

   docker build -t dpg_dockerfile -f dockerfile .
   

   If you get a permissions error on running this command, you may need to run it with sudo:

   sudo docker build -t dpg_dockerfile -f dockerfile .
   

5. Run Docker from the Dockerfile you've just built

   docker run -it -p 8888:8888 -p 6006:6006 dpg_dockerfile bash
   

   or

   sudo docker run -it -p 8888:8888 -p 6006:6006 dpg_dockerfile bash
   

   if you run into permission problems.

6. Launch Jupyter and Tensorboard both by using tmux

   tmux
   
   jupyter notebook --allow-root
   

   Press CTL+B then C to open a new tmux window, then

   tensorboard --logdir='/tmp/dpg'
   

   To switch windows Press CTL+B then window #

   Once both jupyter and tensorboard are running, using your browser, navigate to the URLs shown in the terminal output if those don't work try http://localhost:8888/ for Jupyter Notebook and http://localhost:6006/ for Tensorboard.

Using Native Python 3

1. Install system requirements

sudo apt-get install git cmake zlib1g-delibjpeg-dev libboost-all-dev libsdl2-dev wget unzip gitboostbuild-essential zlib1g-dev libsdl2-dev libjpeg-dev nasm tar libbz2-dev libgtk2.0-dev cmake libfluidsynth-dev libgme-dev libopenal-dev timidity libwildmidi-dev python3-pip python3-dev python3-wheel

2. Download and unzip this entire repo from GitHub, either interactively, or by entering

git clone https://github.com/wagonhelm/Deep-Policy-Gradient.git

3. Install Python Requirement

cd Deep-Policy-Gradient
pip3 install -r requirements.txt
pip3 install tensorflow jupyter

4. Launch Jupyter

jupyter notebook

5. Launch Tensorboard

tensorboard --logdir='/tmp/dpg'

Once both jupyter and tensorboard are running, using your browser, navigate to the URLs shown in the terminal output if those don't work try http://localhost:8888/ for Jupyter Notebook and http://localhost:6006/ for Tensorboard.