• DocumentCode
    2390170
  • Title

    Selective relaxation for constraint satisfaction problems

  • Author

    Freuder, E.C. ; Wallace, R.J.

  • Author_Institution
    Dept. of Comput. Sci., New Hampshire Univ., Durham, NH, USA
  • fYear
    1991
  • fDate
    10-13 Nov 1991
  • Firstpage
    332
  • Lastpage
    339
  • Abstract
    A basic problem is to optimize the tradeoff between effort required to establish a local consistency and that required for search. An approach is presented to this problem which is termed selective relaxation. The idea is to perform consistency checking at places where it is likely to be effective, basing this judgment on local criteria. To this end, the authors introduce two forms of bounded relaxation, one in which consistency testing propagates for a limited distance from a point of change, and one in which it stops when the amount of change, or response, falls below threshold. Experiments show that these procedures can outperform well-known preprocessing or hybrid algorithms on many problems
  • Keywords
    artificial intelligence; constraint theory; bounded relaxation; consistency checking; constraint satisfaction problems; hybrid algorithms; local consistency; local criteria; selective relaxation; Artificial intelligence; Computer science; Data preprocessing; Performance evaluation; Relaxation methods; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-8186-2300-4
  • Type

    conf

  • DOI
    10.1109/TAI.1991.167112
  • Filename
    167112