Autonomous Bidding Agents

Strategies and Lessons from the Trading Agent Competition
Erscheinungsjahr 2007
ISBN: 978-0-262-23260-9
Verlag: MIT Press Ltd

Buch, Englisch, 250 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 499 g

Reihe: Intelligent Robotics and Autonomous Agents series

Overview and analysis of algorithmic advances developed within an integrated bidding agent architecture that emerged from recent research in a growing domain of AI.

E-commerce increasingly provides opportunities for autonomous bidding agents: computer programs that bid in electronic markets without direct human intervention. Automated bidding strategies for an auction of a single good with a known valuation are fairly straightforward; designing strategies for simultaneous auctions with interdependent valuations is a more complex undertaking. This book presents algorithmic advances and strategy ideas within an integrated bidding agent architecture that have emerged from recent work in this fast-growing area of research in academia and industry. The authors analyze several novel bidding approaches that developed from the Trading Agent Competition (TAC), held annually since 2000. The benchmark challenge for competing agents—to buy and sell multiple goods with interdependent valuations in simultaneous auctions of different types—encourages competitors to apply innovative techniques to a common task. The book traces the evolution of TAC and follows selected agents from conception through several competitions, presenting and analyzing detailed algorithms developed for autonomous bidding. Autonomous Bidding Agents provides the first integrated treatment of methods in this rapidly developing domain of AI. The authors—who introduced TAC and created some of its most successful agents—offer both an overview of current research and new results.

Autoren/Hrsg.

Wellman, Michael P.

Greenwald, Amy

Stone, Peter

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Sonstige Wirtschaftssektoren & Branchen
• Mathematik | Informatik EDV | Informatik Informatik
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Wirtschaftssektoren & Branchen: Allgemeines
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Handwerk

Über Autor(innen)

Greenwald, Amy
Amy Greenwald is Assistant Professor of Computer Science at Brown
University.

Wellman, Michael P.
Michael P. Wellman is Professor of Computer Science and Engineering and member of
the Artificial Intelligence Laboratory at the University of Michigan, Ann
Arbor.

Stone, Peter
Peter Stone is Assistant Professor of Computer Sciences, Alfred P. Sloan Research
Fellow, and Director of the Learning Agents Group, University of Texas at Austin. He
is the recipient of the International Joint Conference on Artificial Intelligence
(IJCAI) 2007 Computers and Thought Award.

Amy Greenwald is Assistant Professor of Computer Science at Brown University.