• DocumentCode
    1048566
  • Title

    Expected-outcome: a general model of static evaluation

  • Author

    Abramson, Bruce

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    12
  • Issue
    2
  • fYear
    1990
  • fDate
    2/1/1990 12:00:00 AM
  • Firstpage
    182
  • Lastpage
    193
  • Abstract
    The expected-outcome model, in which the proper evaluation of a game-tree node is the expected value of the game´s outcome given random play from that node on, is proposed. Expected outcome is considered in its ideal form, where it is shown to be a powerful heuristic. The ability of a simple random sampler that estimates expected outcome to outduel a standard Othello evaluator is demonstrated. The sampler is combined with a linear regression procedure to produce efficient expected-outcome estimators. Overall, the expected-outcome model of two-player games is shown to be precise, accurate, easily estimable, efficiently calculable, and domain-independent
  • Keywords
    artificial intelligence; game theory; Othello evaluator; artificial intelligence; decision making; expected-outcome model; game theory; game-tree node; heuristic; linear regression; Analytical models; Computational modeling; Decision making; Game theory; Learning systems; Linear regression; Machine learning; Minimax techniques; Performance evaluation; Probability;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.44404
  • Filename
    44404