UMBCTAC: A Balanced Bidding Agent

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https://ebiquity.umbc.edu/paper/html/id/140/UMBCTAC-A-Balanced-Bidding-Agent

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http://hdl.handle.net/11603/12326

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UMBC Computer Science and Electrical Engineering Department
UMBC Student Collection

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2002-12-14

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technical reports
Text

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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

balance heuristic
early bird heuristic
trading agent competition (TAC)
UMBC Ebiquity Research Group

Abstract

UMBCTAC is one of the top ranking agents in the 3rd International Trading Agent Competition (TAC). A TAC game has multiple auctions running on different but interrelated resources simultaneously, and 8 trading agents will compete with each other for optimal result – making maximum profit. The spirit of simplicity and balance is used as a guideline to solve the dynamical optimization problem in TAC game. The hotel/airline auctions and the entertainment ticket auctions are handled separately by applying early bird heuristic. A gain-risk model is used to select a good, safe resource allocation for the clients in hotel/airline auctions. A fast and simple probabilistic approach is used to handle entertainment ticket auctions.