• DocumentCode
    1684982
  • Title

    A hybrid Artificial Intelligence approach with application to games

  • Author

    Cant, Richard ; Churchill, Julian ; Al-Dabass, David

  • Author_Institution
    Dept. of Comput. & Math., Nottingham Trent Univ., UK
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1575
  • Lastpage
    1580
  • Abstract
    We describe a hybrid Artificial Intelligence (AI) approach combining soft AI techniques (neural networks) and hard AI methods (alpha-beta game tree search), in an attempt to approximate human play more accurately, in particular with reference to the game of Go. The program is tested and analysed by play against another Go playing program and it is shown that the use of hard AI enhances the performance of the soft AI system and vice-versa
  • Keywords
    artificial intelligence; feedforward neural nets; game theory; tree searching; alpha-beta game tree search; game of Go; hard AI methods; hybrid artificial intelligence approach; neural networks; soft AI techniques; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological system modeling; Brain modeling; Computer networks; Humans; Neural networks; Neurons; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007752
  • Filename
    1007752