For overall project summary click here
Cloning Steps:
git clone --recursive -j8 git@github.com:VineetTambe/multi-agent-rl.git
It is recomended that you create a python virtual environment and install the following packages.
cd gym-multigrid/ && pip install -e .
cd ..
cd rl-baselines3-zoo/ && pip install -e . && pip install -r requirements.txt
If you face any errors while install box2d run the following -
sudo apt install swig
pip install -r requirements.txt
cd to the rl-baselines3-zoo
repository and run the following command:
python3 train.py --env multigrid-mapf-v0 -lb ./logs/ppo/ --algo ppo --env-kwargs scenario_file:\'/home/vineet/competition/Start-Kit/example_problems/warehouse.domain/warehouse_small_10.json\'
python3 train.py -tb ./logs/ppo/ --env multigrid-mapf-v0 --conf-file ./hyperparams/python/ppo_cnn_config.py --algo ppo --env-kwargs scenario_file:\'/home/admin/multi-agent-rl/Start-Kit/example_problems/warehouse.domain/warehouse_small_10.json\' agent_view_size:40
The training params are located in the hyperparams
folder in rl-baselines3-zoo
directory - you can update the params for the algorithm being used here.
cd to the rl-baselines3-zoo
repository and run the following command:
You will have to modify the following lines 87 - 90
The model.predict code is at 215 - 225
python3 custom_runner.py
cd to the rl-baselines3-zoo
repository and run the following command:
python3 enjoy.py --env multigrid-mapf-v0 --algo ppo --env-kwargs scenario_file:\'/home/vineet/competition/Start-Kit/example_problems/warehouse.domain/warehouse_small_10.json\' -f logs/ --exp-id 2 --load-best