ATTac-2001: A learning, autonomous bidding agent

Peter Stone, Robert E. Schapire, János A. Csirik, Michael L. Littman, David McAllester

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations


Auctions are becoming an increasingly popular method for transacting business, especially over the Internet. This paper presents a general approach to building autonomous bidding agents to bid in multiple simultaneous auctions for interacting goods. The core of our approach is learning a model of the empirical price dynamics based on past data and using the model to analytically calculate, to the greatest extent possible, optimal bids. This approach is fully implemented as ATTac-2001, a top-scoring agent in the second Trading Agent Competition (TAC-01). ATTac-2001 uses boosting techniques to learn conditional distributions of auction clearing prices.We present experiments demonstrating the effectiveness of this predictor relative to several reasonable alternatives.

Original languageEnglish (US)
Title of host publicationAgent-Mediated Electronic Commerce IV
Subtitle of host publicationDesigning Mechanisms and Systems - AAMAS 2002 Workshop on Agent-Mediated Electronic Commerce, Revised Papers
EditorsJulian Padget, Onn Shehory, David Parkes, Norman Sadeh, William E. Walsh
PublisherSpringer Verlag
Number of pages18
ISBN (Print)9783540003274
StatePublished - 2002
Externally publishedYes
EventWorkshop on Agent-Mediated Electronic Commerce, AAMAS 2002 - Bologna, Italy
Duration: Jul 16 2002Jul 16 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceWorkshop on Agent-Mediated Electronic Commerce, AAMAS 2002

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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