• Corpus ID: 139105904

# Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers

@article{Yang2019GraphNR,
title={Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers},
author={Zhanfu Yang and Fei Wang and Ziliang Chen and Guannan Wei and Tiark Rompf},
journal={ArXiv},
year={2019},
volume={abs/1904.12084}
}
• Published 27 April 2019
• Computer Science
• ArXiv
In this paper, we investigate the feasibility of learning GNN (Graph Neural Network) based solvers and GNN-based heuristics for specified QBF (Quantified Boolean Formula) problems. [] Key Method Then we show how to learn a heuristic CEGAR 2QBF solver. We further explore generalizing GNN-based heuristics to larger unseen instances, and uncover some interesting challenges. In summary, this paper provides a comprehensive surveying view of applying GNN-embeddings to specified QBF solvers, and aims to offer…
8 Citations

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