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Walverine: A Walrasian Trading Agent

Listed author(s):
  • Shih-Fen Cheng

    (Univ Michigan)

  • Evan Leung

    (Univ Michigan)

  • Kevin M. Lochner

    (Univ Michigan)

  • Kevin O'Malley

    (Univ Michigan)

  • Daniel M. Reeves

    (Univ Michigan)

  • L. Julian Schvartzman

    (Univ Michigan)

  • Michael P. Wellman

    (Univ Michigan)

TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, bases its decisions on a competitive (Walrasian) analysis of the TAC travel economy. Using this Walrasian model, we construct a decision-theoretic formulation of the optimal bidding problem, which Walverine solves in each round of bidding for each good. Walverine's optimal bidding approach, as well as several other features of its overall strategy, are potentially applicable in a broad class of trading environments.

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Paper provided by EconWPA in its series Computational Economics with number 0302003.

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Length: 23 pages
Date of creation: 25 Feb 2003
Handle: RePEc:wpa:wuwpco:0302003
Note: Type of Document - pdf; pages: 23 . To appear in AAMAS-03. Extended version submitted for publication.
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References listed on IDEAS
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  1. Wurman, Peter R. & Wellman, Michael P. & Walsh, William E., 2001. "A Parametrization of the Auction Design Space," Games and Economic Behavior, Elsevier, vol. 35(1-2), pages 304-338, April.
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