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Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition

Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition

Автор: Michael P. Wellman, Amy Greenwald, Peter Stone, 238 стр., издатель: "The MIT Press", ISBN: 026223260X

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...
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