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This software is a python implementation of Deep Q-Networks for playing ATARI games with Chainer package.

I followed the implementation described in: * V. Mnih et al., "Playing atari with deep reinforcement learning" * V. Mnih et al., "Human-level control through deep reinforcement learning"

For japanese instruction of DQN and historical review, please check:


My implementation is dependent on RL-glue, Arcade Learning Environment, and Chainer. To run the software, you need following softwares/packages.

  • Python 2.7+
  • Numpy
  • Scipy
  • Pillow (PIL)
  • Chainer (1.3.0):
  • RL-glue core:
  • RL-glue Python codec:
  • Arcade Learning Environment (version ALE 0.4.4):

This software was tested on Ubuntu 14.04 LTS.

How to run

Please check readme.txt

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