Publication Type
Journal Article
Version
Publisher’s Version
Publication Date
4-2005
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.
Discipline
Artificial Intelligence and Robotics | Business
Publication
Decision Support Systems
Volume
39
Issue
2
First Page
169
Last Page
184
ISSN
0167-9236
Identifier
10.1016/j.dss.2003.10.005
Publisher
Elsevier
Citation
CHENG, Shih-Fen; LEUNG, Evan; LOCHNER, Kevin M.; O'MALLEY, Kevin; REEVES, Daniel M.; SCHVARTZMAN, Julian L.; and WELLMAN, Michael P..
Walverine: A walrasian trading agent. (2005). Decision Support Systems. 39, (2), 169-184.
Available at: https://ink.library.smu.edu.sg/sis_research/47
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1016/j.dss.2003.10.005