• DocumentCode
    1918515
  • Title

    How hierarchies of objects and constraints reduce complexity

  • Author

    Iordanova, Blaga N.

  • Volume
    1
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    535
  • Abstract
    Hierarchies help learning clearance-categories of flights and organise these knowledge categories in hierarchical structures of objects and constraints. They reduce complexity by introducing levels of decomposition in hierarchical layers of learning objects of clearance-categories and in satisfying constraints. They lower complexity by stressing parallelism in learning and in the formation of concepts of clearances in response to requests. They reduce the search problem into a decision problem.
  • Keywords
    air traffic control; computational complexity; constraint handling; decision theory; learning (artificial intelligence); search problems; air space-time; air traffic knowledge; clearance request; clearance-categories; complexity reduction; constraints; data structures; decomposition level; hierarchical structures; learning; object hierarchies; parallelism; search problem; Air traffic control; Aircraft; Automatic control; Control systems; Knowledge management; Neurons; Resource management; Search problems; Space technology; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223403
  • Filename
    1223403