• DocumentCode
    1940995
  • Title

    Opposition-Based Learning: A New Scheme for Machine Intelligence

  • Author

    Tizhoosh, Hamid R.

  • Author_Institution
    Pattern Anal. & Machine Intelligence Lab., Waterloo Univ., Ont.
  • Volume
    1
  • fYear
    2005
  • fDate
    28-30 Nov. 2005
  • Firstpage
    695
  • Lastpage
    701
  • Abstract
    Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions are the foundation of this new approach. Examples are provided. Possibilities for extensions of existing learning algorithms are discussed. Preliminary results are provided
  • Keywords
    estimation theory; learning (artificial intelligence); optimisation; search problems; machine intelligence; opposition-based learning; Biological neural networks; Computational intelligence; Genetic algorithms; Humans; Intelligent agent; Internet; Learning systems; Machine intelligence; Machine learning; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    0-7695-2504-0
  • Type

    conf

  • DOI
    10.1109/CIMCA.2005.1631345
  • Filename
    1631345
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1940995