• DocumentCode
    2642126
  • Title

    Improved Alpha-Beta Pruning of Heuristic Search in Game-Playing Tree

  • Author

    Zhang Congpin ; Cui-Jinling

  • Author_Institution
    Key Lab. for Intell. Inf. Process., Henan Normal Univ., Xinxiang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    672
  • Lastpage
    674
  • Abstract
    The game playing is an import domain of heuristic search, and its procedure is represented by a special and/or tree. Alpha-beta pruning is always used for problem solving by searching the game-playing-tree. In this paper, the plan which child nodes are inserted into game-playing-tree from large value of estimation function to small one when the node of no receiving fixed ply depth is expand is proposed based on alpha-beta pruning. It improves effect of search.
  • Keywords
    game theory; games of skill; search problems; trees (mathematics); child nodes; estimation function; game-playing tree; heuristic search; improved alpha-beta pruning; Computer science; Educational institutions; Information processing; Information technology; Laboratories; Minimax techniques; Problem-solving; alpha-beta pruning; game playing; heuristic search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.527
  • Filename
    5171424