Combining inference and search for the propositional satisfiability problem

被引:0
|
作者
Drake, L [1 ]
Frisch, A [1 ]
Walsh, T [1 ]
机构
[1] Univ York, Dept Comp Sci, York YO10 5DD, N Yorkshire, England
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The most effective complete method for testing propositional satisfiability (SAT) is backtracking search. Recent research suggests that adding more inference to SAT search procedures can improve their performance. This paper presents two ways to combine neighbour resolution (one such inference technique) with search.
引用
收藏
页码:982 / 982
页数:1
相关论文
共 50 条
  • [31] Using problem symmetry in search based satisfiability algorithms
    Goldberg, EI
    Prasad, MR
    Brayton, RK
    DESIGN, AUTOMATION AND TEST IN EUROPE CONFERENCE AND EXHIBITION, 2002 PROCEEDINGS, 2002, : 134 - 141
  • [32] Local Search Algorithm for the Partial Minimum Satisfiability Problem
    Abrame, Andre
    Habet, Djamal
    2015 IEEE 27TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2015), 2015, : 821 - 827
  • [33] GASAT: A genetic local search algorithm for the satisfiability problem
    Lardeux, Frederic
    Saubion, Frederic
    Hao, Jin-Kao
    EVOLUTIONARY COMPUTATION, 2006, 14 (02) : 223 - 253
  • [34] Local Search Based on Conflict Analysis for the Satisfiability Problem
    Habet, Djamal
    Toumi, Donia
    2012 IEEE 24TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2012), VOL 1, 2012, : 892 - 897
  • [35] Speeding-up non-clausal local search for propositional satisfiability with clause learning
    Stachniak, Zbigniew
    Belov, Anton
    THEORY AND APPLICATIONS OF SATISFIABILITY TESTING - SAT 2008, PROCEEDINGS, 2008, 4996 : 257 - 270
  • [36] Combining solutions of the optimum satisfiability problem using evolutionary tunneling
    da Silva R.F.
    Hvattum L.M.
    Glover F.
    Hvattum, Lars Magnus (hvattum@himolde.no), 1600, Brno University of Technology (26): : 7 - 13
  • [37] Combining cellular genetic algorithms and local search for solving satisfiability problems
    Folino, G
    Pizzuti, C
    Spezzano, G
    TENTH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 1998, : 192 - 198
  • [38] Answer set programming based on propositional satisfiability
    Giunchiglia, Enrico
    Lierler, Yuliya
    Maratea, Marco
    JOURNAL OF AUTOMATED REASONING, 2006, 36 (04) : 345 - 377
  • [39] Answer set programming based on propositional satisfiability
    Giunchiglia, Enrico
    Lierler, Yuliya
    Maratea, Marco
    Journal of Automated Reasoning, 2006, 36 (04): : 345 - 377
  • [40] What is answer set programming to propositional satisfiability
    Lierler, Yuliya
    CONSTRAINTS, 2017, 22 (03) : 307 - 337