• DocumentCode
    2357648
  • Title

    Improving nogood recording using 2SAT

  • Author

    Stuckey, Peter J. ; Zheng, Lei

  • Author_Institution
    Dept. of Comput. Sci. & Software Eng., Melbourne Univ., Vic., Australia
  • fYear
    2003
  • fDate
    3-5 Nov. 2003
  • Firstpage
    94
  • Lastpage
    99
  • Abstract
    Nogood recording is a dynamic learning technique widely applied to solve CSP (constraint satisfaction problems). It is highly effective in reducing the search space for SAT (satisfiability) problems. While SAT is NP-complete, the problem restricted to binary clauses (2SAT) is solvable in linear time. We can improve SAT solving by incorporating 2SAT solving techniques. In this paper we investigate extending nogood recording to make use of binary clause resolution. Our experiments show that nogoods generated from binary resolution can significantly reduce the search space, and size of nogoods generated, as well as the search time.
  • Keywords
    backtracking; computability; computational complexity; constraint theory; learning (artificial intelligence); problem solving; 2SAT; CSP; NP-complete; SAT; binary clause resolution; binary clauses; binary resolution; constraint satisfaction problems; dynamic learning; linear time; nogood recording; satisfiability problems; search space; search time; systems analysis tool; Artificial intelligence; Australia; Computer science; Information analysis; Reactive power; Software engineering; Space exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2038-3
  • Type

    conf

  • DOI
    10.1109/TAI.2003.1250175
  • Filename
    1250175