An implementation of maddpg-pytorch on a multi-agent minigrid environment.
- OpenAI baselines, commit hash: 98257ef8c9bd23a24a330731ae54ed086d9ce4a7
- shariqiqbal2810's fork of Multi-agent Particle Environments
- PyTorch, version: 1.6.0
- OpenAI Gym, version: 0.9.6
- Tensorboard, version: 2.3.0 and tensorboardX, version: 2.1 (for logging)
- My fork of MiniGrid
The versions are just what I used and not necessarily strict requirements.
All training code is contained within main.py
. To view options simply run:
python main.py --help
To train an example in the MiniGrid env:
ma-minigrid-maddpg: python main.py --env_id MiniGrid-MA-UnlockDoorGoalA2-v0 --model_name test_minigrid --discrete_action
To visualize a model from the MiniGrid env:
python evaluate.py --env_id MiniGrid-MA-UnlockDoorGoalA2-v0 --model_name test_minigrid
To train an example in the MPE env:
python main.py --mpe
To visualize a model from the MPE env:
python evaluate.py --mpe
maddpg-pytorch & all acknowledgements from that repo as well.