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Searching for Walverine 2005

  • Michael P. Wellman
  • Daniel M. Reeves
  • Kevin M. Lochner
  • Rahul Suri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3937)

Abstract

We systematically explore a range of variations of our TAC travel-shopping agent, Walverine. The space of strategies is defined by settings to behavioral parameter values. Our empirical game-theoretic analysis is facilitated by approximating games through hierarchical reduction methods. This approach generated a small set of candidates for the version to run in the TAC-05 tournament. We selected among these based on performance in preliminary rounds, ultimately identifying a successful strategy for Walverine 2005.

Keywords

Strategic Interaction Adjusted Score Original Game Candidate Strategy Symmetric Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michael P. Wellman
    • 1
  • Daniel M. Reeves
    • 1
  • Kevin M. Lochner
    • 1
  • Rahul Suri
    • 1
  1. 1.University of MichiganAnn ArborUSA

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