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Robust Cooperative Multi-agent Reinforcement Learning via Multi-view Message Certification

This repository contains the implementation of CroMAC (SCIS), based on PyTorch.

1. Getting started

Use the install script to install the python environment:

conda create -n CroMAC python=3.7 -y
conda activate CroMAC
pip install torch torchvision torchaudio
pip install sacred numpy scipy matplotlib seaborn pyyaml pygame pytest probscale imageio snakeviz tensorboard-logger tensorboard tensorboardx
cd CroMAC
unzip qplex_smac.zip
unzip lb-foraging-master.zip
pip install -e qplex_smac/
pip install -e lb-foraging-master/
pip install gym==0.21.0
pip install importlib-metadata==4.13.0
bash install_sc2.sh
unzip map.zip -d $SC2PATH/Maps/SMAC_MAPS

2. Run an experiment

All the experiments can be run with the unified entrance file src/main.py with customized arguments.

Training scripts are also provided in the runalgo.sh script.

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  • Python 98.6%
  • Shell 1.4%