• DocumentCode
    3061913
  • Title

    Discovery of maximal distance codes using genetic algorithms

  • Author

    Dontas, Kejitan ; De Jong, Kenneth

  • Author_Institution
    Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
  • fYear
    1990
  • fDate
    6-9 Nov 1990
  • Firstpage
    805
  • Lastpage
    811
  • Abstract
    An application of genetic algorithms to the problem of discovering communication codes with properties useful for error corrections is described. Search spaces for these codes are so large as to rule out any exhaustive search strategy. Coding theory provides a rich and interesting domain for genetic algorithms. There are some coding problems about which a lot is known and good codes can be generated systematically. On the other hand, there are problem areas where little can be said about the characteristics of the codes in advance. Genetic algorithms have been advocated for these kinds of problems where domain knowledge is either limited or hard to represent and formalize. The authors describe some initial experiments on the use of genetic algorithms to discover maximal distance codes, and discuss the potential advantage of genetic algorithms in this problem domain
  • Keywords
    error correction codes; genetic algorithms; coding problems; communication codes; domain knowledge; error corrections; genetic algorithms; maximal distance codes; search strategy; Application software; Artificial intelligence; Computer science; Decoding; Error correction codes; Genetic algorithms; Neural networks; Organisms; Polynomials; Redundancy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools for Artificial Intelligence, 1990.,Proceedings of the 2nd International IEEE Conference on
  • Conference_Location
    Herndon, VA
  • Print_ISBN
    0-8186-2084-6
  • Type

    conf

  • DOI
    10.1109/TAI.1990.130442
  • Filename
    130442