Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets
This volume contains 9 thoroughly refereed and revised papers detailing recent advances in research on designing trading agents and mechanisms for agent-mediated e-commerce. They were originally presented at the 12th International Workshop on Agent-Mediat
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Esther David Kate Larson Alex Rogers Onn Shehory Sebastian Stein (Eds.)
Agent-Mediated Electronic Commerce Designing Trading Strategies and Mechanisms for Electronic Markets
AMEC 2010, Toronto, ON, Canada, May 10, 2010 and TADA 2010, Cambridge, MA, USA, June 7, 2010 Revised Selected Papers
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Volume Editors Esther David Ashkelon Academic College Ashkelon, Israel E-mail: [email protected] Kate Larson University of Waterloo Waterloo, ON, Canada E-mail: [email protected] Alex Rogers University of Southampton Southampton, UK E-mail: [email protected] Onn Shehory IBM Haifa Research Lab Haifa, Israel E-mail: [email protected] Sebastian Stein University of Southampton Southampton, UK E-mail: [email protected]
ISSN 1865-1348 e-ISSN 1865-1356 ISBN 978-3-642-34199-1 e-ISBN 978-3-642-34200-4 DOI 10.1007/978-3-642-34200-4 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012949470 ACM Computing Classification (1998): K.4.4, J.1, I.2.11, H.3.5
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Preface
Enabled by the increasing processing power of computers and the pervasive interconnectivity of the Internet, automatic trading has become a ubiquitous feature of modern marketplaces. Investors use intelligent algorithms to trade stocks and currencies in global markets, businesses participate in complex automated supply chains, and advertisers bid dynamically for the attention of individual Web users. The benefits of using autonomous software components, or agents, in these settings are manifold. Unlike their human counterparts, trading agents are able to react almost instantaneously to changing circumstances, quickly process and fuse digital data from many diverse sources, and potentially complete millions of transactions per second. However, our growing reliance on automated trading agents raises many pressing research challenges. At the level of the individual agent, we need to design effective decision-making algorithms that achieve their own
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