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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.
List of contents
Section I: Automated Negotiation.- Automated Negotiation and Bundling of Information Goods.- Two Stock-Trading Agents: Market Making and Technical Analysis.- Acquiring Tradeoff Preferences for Automated Negotiations: A Case Study.- A Decommitment Strategy in a Competitive Multi-agent Transportation Setting.- Section II: Mechanism Design.- Sequences of Take-It-or-Leave-It Offers: Near-Optimal Auctions Without Full Valuation Revelation.- Mechanism for Optimally Trading Off Revenue and Efficiency in Multi-unit Auctions.- Choosing Samples to Compute Heuristic-Strategy Nash Equilibrium.- Section III: Multi-agent Markets.- Improving Learning Performance by Applying Economic Knowledge.- Handling Resource Use Oscillation in Multi-agent Markets.
