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Autonomous Bidding Agents Strategies And Lessons From The Trading Agent Competition Michael P Wellman Amy Greenwald Peter Stone

  • SKU: BELL-56575964
Autonomous Bidding Agents Strategies And Lessons From The Trading Agent Competition Michael P Wellman Amy Greenwald Peter Stone
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Autonomous Bidding Agents Strategies And Lessons From The Trading Agent Competition Michael P Wellman Amy Greenwald Peter Stone instant download after payment.

Publisher: MIT Press
File Extension: PDF
File size: 2.2 MB
Author: Michael P. Wellman & Amy Greenwald & Peter Stone
ISBN: 9780262232609, 026223260X
Language: English
Year: 2007

Product desciption

Autonomous Bidding Agents Strategies And Lessons From The Trading Agent Competition Michael P Wellman Amy Greenwald Peter Stone by Michael P. Wellman & Amy Greenwald & Peter Stone 9780262232609, 026223260X instant download after payment.

E-commerce increasingly provides opportunities for autonomous bidding agents:computer programs that bid in electronic markets without direct human intervention. Automatedbidding strategies for an auction of a single good with a known valuation are fairlystraightforward; designing strategies for simultaneous auctions with interdependent valuations is amore complex undertaking. This book presents algorithmic advances and strategy ideas within anintegrated bidding agent architecture that have emerged from recent work in this fast-growing areaof research in academia and industry. The authors analyze several novel bidding approaches thatdeveloped from the Trading Agent Competition (TAC), held annually since 2000. The benchmarkchallenge for competing agents--to buy and sell multiple goods with interdependent valuations insimultaneous auctions of different types--encourages competitors to apply innovative techniques to acommon task. The book traces the evolution of TAC and follows selected agents from conceptionthrough several competitions, presenting and analyzing detailed algorithms developed for autonomousbidding. Autonomous Bidding Agents provides the first integrated treatment of methods in thisrapidly developing domain of AI. The authors--who introduced TAC and created some of its mostsuccessful agents--offer both an overview of current research and new results. Michael P. Wellman isProfessor of Computer Science and Engineering and member of the Artificial Intelligence Laboratoryat the University of Michigan, Ann Arbor. Amy Greenwald is Assistant Professor of Computer Scienceat Brown University. Peter Stone is Assistant Professor of Computer Sciences, Alfred P. SloanResearch Fellow, and Director of the Learning Agents Group at the University of Texas, Austin. He isthe recipient of the International Joint Conference on Artificial Intelligence (IJCAI) 2007Computers and Thought Award.
ISBN : 9780262232609

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