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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

End-to-end SAT assignment model based on instance related characteristics of SAT

Long Zhengrong
Li Jinlong
Liang Yonghao
School of Computer Science & Technology, University of Science & Technology of China, Hefei Anhui 230026, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0096

Abstract

Recently, the neural network-based end-to-end SAT solver shows great potential in predicting the solution of SAT instances. However, SAT solvers do not accept any error, and the prediction error of neural network-based models is not inevitable. Aiming at the problem of the SAT does not allow for errors, this paper proposes an error preference variable embedding adjustment algorithm and a dynamic partial label supervised training mode to reduce the model prediction error by exploiting the properties of the SAT instance. First, to take advantage of the characteristic that the more unsatisfied clauses a variable participates in, the more likely it is to be misclassified, this paper proposes an error preference variable embedding adjustment algorithm, which is used during the message passing process to adjust the embedding of a variable according to the number of unsatisfied clauses it participates in. In addition, this paper proposes a dynamic partial label supervised training mode, which exploits the feature of complex dependencies among variable assignments for SAT instances, avoiding to provide labels for all the variables, and providing only a set of labels from a solution for the error-preference variables, and keeping the other variables' label as the predictions unchanged, which manages a smaller search space during the training. Finally, this paper presents experimental validation on 3-SAT, k-SAT, k-Coloring, 3-Clique, SHA-1 pre-image attack, and the collected SAT competition dataset. The results show that compared to the SOTA end-to-end model QuerySAT, AEEV improves the accuracy by 45.81% on the k-SAT dataset with 600 variables.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0096
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-08-05] Accepted Paper

Cite This Article

龙峥嵘, 李金龙, 梁永濠. 基于SAT问题实例特性的端到端SAT求解模型 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0096. (Long Zhengrong, Li Jinlong, Liang Yonghao. End-to-end SAT assignment model based on instance related characteristics of SAT [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0096. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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