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

Contributor(s): Faratin, Peyman [editor.] | Parkes, David C [editor.] | Rodríguez-Aguilar, Juan A [editor.] | Walsh, William E [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 3048Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2004.Description: VII, 153 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540259473.Subject(s): Computer science | Artificial intelligence | E-commerce | Economic theory | Computer Science | Artificial Intelligence (incl. Robotics) | Economic Theory/Quantitative Economics/Mathematical Methods | e-Commerce/e-businessOnline resources: Click here to access online
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.
In: Springer eBooks
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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.

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