Learning for Dynamic Subsumption

被引:10
|
作者
Hamadi, Youssef [1 ]
Jabbour, Said [2 ]
Sais, Lakhdar [2 ]
机构
[1] Microsoft Res, 7 JJ Thomson Ave, Cambridge, England
[2] Univ Lille Nord France, CRIL, CNRS, UMR 8188, F-59655 Villeneuve Dascq, France
关键词
D O I
10.1109/ICTAI.2009.22
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an original dynamic subsumption technique for Boolean CNF formulae. It exploits simple and sufficient conditions to detect, during conflict analysis, clauses from the formula that can be reduced by subsumption. During the learnt clause derivation, and at each step of the associated resolution process, checks for backward subsumption between the current resolvent and clauses from the original formula are efficiently performed. The resulting method allows the dynamic removal of literals from the original clauses. Experimental results show that the integration of our dynamic subsumption technique within the state-of-the-art SAT solvers Minisat and Rsat particularly benefits to crafted problems.
引用
收藏
页码:328 / +
页数:2
相关论文
共 50 条
  • [31] Quantifying sequential subsumption
    Wang, Hui
    Elzinga, Cees H.
    Lin, Zhiwei
    Vincent, Jordan
    THEORETICAL COMPUTER SCIENCE, 2019, 793 (79-99) : 79 - 99
  • [32] Generalized Mutant Subsumption
    Al Blwi, Samia
    Marsit, Imen
    Khaireddine, Besma
    Ayad, Amani
    Loh, JiMeng
    Mili, Ali
    PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGIES (ICSOFT), 2022, : 46 - 56
  • [33] Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning
    Fei Zheng
    Geoffrey I. Webb
    Pramuditha Suraweera
    Liguang Zhu
    Machine Learning, 2012, 87 : 93 - 125
  • [34] Domain taxonomy learning from text: The subsumption method versus hierarchical clustering
    de Knijff, Jeroen
    Frasincar, Flavius
    Hogenboom, Frederik
    DATA & KNOWLEDGE ENGINEERING, 2013, 83 : 54 - 69
  • [35] UNDECIDABILITY OF SUBSUMPTION IN NIKL
    PATELSCHNEIDER, PF
    ARTIFICIAL INTELLIGENCE, 1989, 39 (02) : 263 - 272
  • [36] EFFICIENT SUBSUMPTION ALGORITHMS
    LEITSCH, A
    JOURNAL OF SYMBOLIC LOGIC, 1987, 52 (01) : 328 - 329
  • [37] Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning
    Zheng, Fei
    Webb, Geoffrey I.
    Suraweera, Pramuditha
    Zhu, Liguang
    MACHINE LEARNING, 2012, 87 (01) : 93 - 125
  • [38] SUBSUMPTION IN KNOWLEDGE GRAPHS
    WILLEMS, M
    LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 1991, 567 : 56 - 66
  • [39] ON THE EFFICIENCY OF SUBSUMPTION ALGORITHMS
    GOTTLOB, G
    LEITSCH, A
    JOURNAL OF THE ACM, 1985, 32 (02) : 280 - 295
  • [40] Mutant Subsumption Graphs
    Kurtz, Bob
    Ammann, Paul
    Delamaro, Marcio E.
    Offutt, Jeff
    Deng, Lin
    2014 SEVENTH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW 2014), 2014, : 176 - 185