This code is implemented based on EPyMARL, and the running instructions are similar to that in the original project. We incorporate Hallway
, LBF
and Traffic Junction
in this code, which you can experiment with config instructions like env-config=hallway/lbf/traffic_junction
. Besides, we incorporte an implementation of Full-Comm
which you can try by setting config=full_comm
in your instruction.
For example, you can run MASIA
on traffic_junction (medium) by using:
python3 src/main.py --config=masia --env-config=traffic_junction
and you can run Full-Comm
on LBF (11x11-6p-4f-1s) by using:
python3 src/main.py --config=full_comm --env-config=lbf with env_args.sight=1 env_args.players=6 env_args.field_size=11 env_args.max_food=4 env_args.force_coop=False
This code will use tensorboard and save model by default, which will be saved in ./results/