Agent-Mediated Electronic Commerce V: Designing Mechanisms and Systems, AAMAS 2003 Workshop, AMEC 2003, Melbourne, Australia, July 15. 2003, Revised Selected Papers

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Peyman Faratin, David C. Parkes, Juan A. Rodríguez-Aguilar, William E. Walsh
Springer Science & Business Media, Oct 18, 2004 - Computers - 153 pages
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The design of intelligent trading agents, mechanisms, and systems has received growingattentionin the agentsandmultiagentsystemscommunities in ane?ort to address the increasing costs of search, transaction, and coordination which follows from the increasing number of Internet-enabled distributed electronic markets. Furthermore, new technologies and supporting business models are - sulting in a growing volume of open and horizontally integrated markets for trading of an increasingly diverse set of goods and services. However, growth of technologies for such markets requires innovative solutions to a diverseset of - isting and novel technical problems which we are only beginning to understand. Speci?cally, distributed markets present not only traditional economic problems but also introduce novel and challenging computational issues that are not r- resentedin the classiceconomicsolution concepts.Novelto agent-mediatedel- tronic commerce are considerations involving the computation substrates of the agents and the electronic institutions that supports, and trading, and also the human-agent interface (involving issues of preference elicitation, representation, reasoningandtrust).Insum, agent-mediatedelectronictraderequiresprincipled design(fromeconomicsandgametheory)andincorporatesnovelcombinationsof theories from di?erent disciplines such as computer science, operations research, arti?cial intelligence and distributed systems. The collection of above-mentioned issues and challenges has crystallized into a new, consolidated agent research ?eld that has become a focus of attention in recent years: agent-mediated electronic commerce.
 

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Contents

Automated Negotiation and Bundling of Information Goods
1
Market Making and Technical Analysis
18
A Case Study
37
A Decommitment Strategy in a Competitive Multiagent Transportation Setting
56
NearOptimal Auctions Without Full Valuation Revelation
73
Mechanism for Optimally Trading Off Revenue and Efficiency in Multiunit Auctions
92
Choosing Samples to Compute HeuristicStrategy Nash Equilibrium
109
Improving Learning Performance by Applying Economic Knowledge
124
Handling Resource Use Oscillation in Multiagent Markets
145
Author Index
154
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