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Walverine: A Walrasian Trading Agent

Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, L. Julian Schvartzman and Michael Wellman ()
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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

Computational Economics from University Library of Munich, Germany

Abstract: 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.

Keywords: trading agent; trading competition; tatonnement; competitive equilibrium (search for similar items in EconPapers)
JEL-codes: C6 D58 C72 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mic
Date: 2003-02-25
Note: Type of Document - pdf; pages: 23 . To appear in AAMAS-03. Extended version submitted for publication.
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