The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems

Official Repository for the paper titled "The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems"

Setup

conda create --name <env> --file <this file>

Install pytorch

Run

Run as

python train.py -d pancake -n 15 -m 4 -o pancake/set_2 -i 1000000

More information about the command line parameters can be obtained as

python train.py --help

Experiments for different loss threshold can be obtained by changing threshold on line 19

Experiments on fixed depth can be obtained by changing on line 360

replace search_width search_depth 

Citing

If you found our repository/experiments useful please consider citing our work as:

@article{
pendurkar2023the,
title={The (Un)Scalability of Informed Heuristic Function Estimation in {NP}-Hard Search Problems},
author={Sumedh Pendurkar and Taoan Huang and Brendan Juba and Jiapeng Zhang and Sven Koenig and Guni Sharon},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2023},
url={https://openreview.net/forum?id=JllRdycmLk},
note={}
}