Predicting Propositional Satisfiability Based on Graph Attention Networks
Abstract Boolean satisfiability problems (SAT) have very rich generic and domain-specific structures. How to capture these structural features in the embedding space and feed them to deep learning models is an important factor influencing the use of neural networks to solve SAT problems. Graph neura...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer
2022-09-01
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| coleção: | International Journal of Computational Intelligence Systems |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/s44196-022-00139-9 |
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