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Google Football Research

MIT License
This is the pytorch example of the google football research, more contents will be updated soon!:soccer:

Requirements

  • python-3.6.8
  • openai-baselines
  • pytorch-1.1.0
  • gfootball

TODO List

  • add more tasks and examples - full game is in plan.
  • remove openai-baseline's functions.
  • add more algorithms: IMPALA and Ape-X DQN.
  • add multi-agent reinforcement learning algorithms (MARL)

Installation

Please install the gfootball according to the instructions here.

  1. Make sure your pip is less than 19, the lastest version of pip will disable --process-dependency-links.
conda install pip==18.1
  1. Install tensorflow (well, we don't need it, but it's required for gfootball).
pip install tensorflow
  1. Install gfootball.
git clone https://github.com/google-research/football.git
cd football
pip install .[tf_cpu] --process-dependency-links (we don't need GPU for tensorflow)

How to use the code

Train the simple example - academy_empty_goal_close

python train_example.py --cuda (if you have a GPU)

Play the demo:

python demo.py

Demo

academy_empty_goal_close academy_run_to_score
academy_3_vs_1_with_keeper academy_counterattack_easy

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It's the pytorch implementation of google research football.

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