This repository contains code for the following publication, please cite our work if you use this repo:

B. Riviere, W. Hönig, M. Anderson, S-J. Chung. "Neural Tree Expansion for Multi-Robot Planning in Non-Cooperative Environments" in IEEE Robotics and Automation Letters (RA-L) June 2021.

Developed on Ubuntu 20.04. Python dependencies in ~/environment.yml, can be batch installed with:

conda env create -f environment.yml

If package install fails, try removing specific versions in .yml file: e.g. if

ResolvePackageNotFound: 
  - libgfortran-ng==7.5.0=hdf63c60_6

change libgfortran-ng==7.5.0=hdf63c60_6 to libgfortran-ng=7.5.0.

Then:

conda activate dm_env

from ~/code/cpp:

mkdir build
cd build
cmake -DPYTHON_EXECUTABLE=$(which python) -DCMAKE_BUILD_TYPE=Release ..
make

Run individual problems and solvers from ~\code by modifying code/param.py and then:

python run.py

Run batch examples from ~\code\tests:

python regression.py

Run waypoint planning from ~\code\tests:

python waypoint_planning.py

Train neural networks by modifying parameters in code/train.py then, from ~\code:

python train.py

If you get an error message such as:

No such file or directory: '/home/ben/projects/decision_making/saved/example9/model_value_l0.pt

it means that the solver tried to query a neural network oracle that does not exist. You can either disable neural network search or create a new model.

To disable the neural network search, change oracles_on in param.py to oracles_on = False

To create a model, run python train.py. After training, you can query the newly created model (in ../current/models/) by changing the dirname parameter in param.py to the corresponding location.