Enhancing Multi-Agent Coordination via Dual-Channel Consensus

This is the implementation of the paper "Enhancing Multi-Agent Coordination via Dual-Channel Consensus" written in PyTorch.

Installation instructions

Set up StarCraft II and SMAC:

bash install_sc2.sh

This will download StarCraft II into the 3rdparty folder and copy the maps necessary to run over. You may also need to set the environment variable for SC2:

export SC2PATH=[Your SC2 folder like /abc/xyz/3rdparty/StarCraftII]

Install Python environment with requirements.txt of pip:

pip install -r requirements.txt

Run an experiment

python3 main.py --config=[Algorithm name] --env-config=[Env name] with env_args.map_name=[Map name if choosing SC2 env]

The config files act as defaults for an algorithm or environment.

All results will be stored in the logs folder.

For example, run DuCC with QMIX mixing network (default SC2 evaluation in the paper) :

python3 main.py --config=qmix --env-config=sc2 with env_args.map_name=3m