Thomas Fournier, Arnaud Lallouet, Télio Cropsal, Gaël Glorian, Alexandre Papadopoulos, Antoine Petitet, Guillaume Perez, Suruthy Sekar, Wijnand Suijlen. A Deep Reinforcement Learning Heuristic for SAT based on Antagonist Graph Neural Networks. In Marek Z. Reformat, Du Zhang, Nikolaos G. Bourbakis, editors, 34th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2022, Macao, China, October 31 - November 2, 2022. pages 1218-1222, IEEE, 2022. [doi]
@inproceedings{FournierLCGPPPSS22,
title = {A Deep Reinforcement Learning Heuristic for SAT based on Antagonist Graph Neural Networks},
author = {Thomas Fournier and Arnaud Lallouet and Télio Cropsal and Gaël Glorian and Alexandre Papadopoulos and Antoine Petitet and Guillaume Perez and Suruthy Sekar and Wijnand Suijlen},
year = {2022},
doi = {10.1109/ICTAI56018.2022.00185},
url = {https://doi.org/10.1109/ICTAI56018.2022.00185},
researchr = {https://researchr.org/publication/FournierLCGPPPSS22},
cites = {0},
citedby = {0},
pages = {1218-1222},
booktitle = {34th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2022, Macao, China, October 31 - November 2, 2022},
editor = {Marek Z. Reformat and Du Zhang and Nikolaos G. Bourbakis},
publisher = {IEEE},
isbn = {979-8-3503-9744-4},
}