PLOI
This repository houses code for the AAAI 2021 paper:
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks
Tom Silver*, Rohan Chitnis*, Aidan Curtis, Joshua Tenenbaum, Tomas Lozano-Perez, Leslie Pack Kaelbling.
For any questions or issues with the code, please email ronuchit@mit.edu and tslvr@mit.edu.
Link to paper: https://arxiv.org/abs/2009.05613
Link to video: https://www.youtube.com/watch?v=FWsVJc2fvCE
Instructions for running (tested on Mac and Linux):
- Use Python 3.6 or higher.
- Download Python dependencies:
pip install -r requirements.txt
. - Make sure the directory containing this code is in your PYTHONPATH.
- Download and build the plan validation tool available at https://github.com/KCL-Planning/VAL, then make a symlink called
validate
on your path that points to thebuild/Validate
binary, e.g.ln -s <path to VAL>/build/Validate /usr/local/bin/validate
. If done successfully, runningvalidate
on your command line should give an output that starts with the line: "VAL: The PDDL+ plan validation tool".
Now, ./run.sh
should work. Different domains and methods can be run by modifying the variables at the top of run.sh.