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Simultaneously searching with multiple algorithm settings: an alternative to parameter tuning for suboptimal single-agent search

  • Author / Creator
    Valenzano, Richard
  • Many single-agent search algorithms have parameters that need to be tuned. Although settings found by offline tuning will exhibit strong average performance, properly selecting parameter settings for each problem can result in substantially reduced search effort. We consider the use of dovetailing as a way to deal with this issue. This procedure performs search with multiple parameter settings simultaneously. We present results testing the use of dovetailing with the weighted A*, weighted IDA*, weighted RBFS, and BULB algorithms on the sliding tile and pancake puzzle domains. Dovetailing will be shown to significantly improve weighted IDA*, often by several orders of magnitude, and generally enhance weighted RBFS. In the case of weighted A* and BULB, dovetailing will be shown to be an ineffective addition to these algorithms. A trivial parallelization of dovetailing will also be shown to decrease the search time in all considered domains.

  • Subjects / Keywords
  • Graduation date
    2009-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R37Q55
  • 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)
    • Sturtevant, Nathan (Computing Science)
    • Schaeffer, Jonathan (Computing Science)
  • Examining committee members and their departments
    • Schaeffer, Jonathan (Computing Science)
    • Liu, Andy (Mathematical and Statistical Sciences)
    • Sturtevant, Nathan (Computing Science)
    • Bulitko, Vadim (Computing Science)