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The aim of this project is the development of intelligent agents which are able to play atari games.

Technologies

  • Python3
  • OpenCV
  • Tensorflow
  • OpenAI Gym - Atari

Models after 48 hours of training

Pong Breakout SpaceInvaders MsPacman

Installation

  • Get Python3. If you are using Anaconda simply type conda create -n atari36 python=3.6)

  • Activate virtual env source activate atari36

  • Install dependencies pip install numpy scipy tensorflow opencv-python gym atari-py Pillow PyOpenGL

  • For Windows refer here https://github.com/j8lp/atari-py to install atari environment

  • On Linux you can get Intel optimized tensorflow wheel:

      pip install https://anaconda.org/intel/tensorflow/1.4.0/download/tensorflow-1.4.0-cp36-cp36m-linux_x86_64.whl

Usage

To train the model:

python start_atari_dqn.py -g Pong-v0

The model is saved to %GAME_ID%/my_dqn.ckpt by default. To view it in action, run:

python start_atari_dqn.py -r -t

For more options:

python tiny_dqn.py --help

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