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Abstraction in Large Extensive Games

  • Author / Creator
    Waugh, Kevin
  • For zero-sum games, we have efficient solution techniques. Unfortunately, there are interesting games that are too large to solve. Here, a popular approach is to solve an abstract game that models the original game. We assume that more accurate the abstract games result in stronger strategies. There is substantial evidence to support this assumption. We begin by formalizing abstraction and refinement, a notion of expressive power for abstractions. We then show the assumption fails to hold under two criteria. The first is exploitability, which measures performance in the worst-case. The second is called the domination value, which measures how many mistakes a strategy makes. Despite these pathologies, we notice that larger strategies tend to make fewer mistakes and perform better in tournaments. Finally, we introduce strategy grafting, a technique that uses sub-game decomposition, which allow us to create good strategies in much larger spaces than previously possible.

  • Subjects / Keywords
  • Graduation date
    2009-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3CM74
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Schuurmans, Dale (Computing Science)
    • Bowling, Michael (Computing Science)
  • Examining committee members and their departments
    • Hooper, Peter (Mathematics and Statistics)
    • Sturtevant, Nathan (Computing Science)