Awesome

Reinforcement learning in 3D

Implemented DQN [3] and A3C [4] algorithm for ViZDoom [1] and DeepMind Lab [2] environments.

Small network on small screen resolution trained relatively fast on simple maps:

• DQN on 1 GPU: ~ 5 minutes on ViZDoom map simpler_basic.
• DQN on 1 GPU: ~ 5 hours on DeepMind Lab map seekavoid_arena_01.
• A3C on 1 CPU, 3 threads: ~13 minutes on ViZDoom map simpler_basic.
• A3C on 1 GPU, 3 workers: ~8 minutes on ViZDoom map simpler_basic.

DQN, ViZDoom map simpler_basic

DQN, DeepMind Lab map seekavoid_arena_01

Dependencies

• numpy
• opencv
• tensorflow
• ViZDoom
• DeepMind Lab

How to run

ViZDoom

• Install ViZDoom and other dependencies
• Set path to it in variable vizdoom_path
• Set variable lab to False
• Set path to rl_3d in path_work_dir
• Run:
  • DQN: ./agent_dqn.py --gpu 0
  • A3C: ./agent_a3c.py

DeepMind Lab

• Install DeepMind Lab and other dependencies
• Set variable lab to True
• Set path to rl_3d in path_work_dir
• For now I used DeepMind Lab build and run system through bazel, so add build rule to lab_path/BUILD (change path_work_dir to your rl_3d path):

py_binary(
    name = "agent_dqn",
    srcs = ["*path_work_dir*/agent_dqn.py"],
    data = [":deepmind_lab.so"],
    main = "*path_work_dir*/agent_dqn.py",
)

py_binary(
    name = "agent_a3c",
    srcs = ["*path_work_dir*/agent_a3c.py"],
    data = [":deepmind_lab.so"],
    main = "*path_work_dir*/agent_a3c.py",
)

• From lab_path run:
  • DQN: bazel run :agent_dqn -- --gpu 0
  • A3C: bazel run :agent_a3c

Thanks

A3C is a little bit tricky algorithm and there are a lot of it's implementations already. So as reference I used implementation by Arthur Juliani.

References

[1] Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, Wojciech Jaśkowski. ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning. arXiv:1605.02097, 2016.

[2] Charles Beattie, Joel Z. Leibo, Denis Teplyashin, Tom Ward, Marcus Wainwright, Heinrich Küttler, Andrew Lefrancq, Simon Green, Víctor Valdés, Amir Sadik, Julian Schrittwieser, Keith Anderson, Sarah York, Max Cant, Adam Cain, Adrian Bolton, Stephen Gaffney, Helen King, Demis Hassabis, Shane Legg, Stig Petersen. DeepMind Lab. arXiv:1612.03801, 2016.

[3] Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller. Playing Atari with Deep Reinforcement Learning. arXiv:1312.5602, 2013.

[4] Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu. Asynchronous Methods for Deep Reinforcement Learning. arXiv:1602.01783, 2016.