Autonomous bidding agents : strategies and lessons from the trading agent competition

著者

    • Wellman, Michael P
    • Greenwald, Amy
    • Stone, Peter

書誌事項

Autonomous bidding agents : strategies and lessons from the trading agent competition

Michael P. Wellman, Amy Greenwald, and Peter Stone

(Intelligent robotics and autonomous agents)

MIT Press, c2007

大学図書館所蔵 件 / 4

この図書・雑誌をさがす

注記

Includes bibliographical references (p. [227]-232) and indexes

内容説明・目次

内容説明

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.

「Nielsen BookData」 より

関連文献: 1件中  1-1を表示

詳細情報

ページトップへ