Designing Mechanisms and Systems, AAMAS 2003 Workshop, AMEC 2003, Melbourne, Australia, July 15. 2003, Revised Selected Papers Redaktion: Faratin, Peyman; Walsh, William E.; Rodríguez-Aguilar, Juan A.; Parkes, David C.
Designing Mechanisms and Systems, AAMAS 2003 Workshop, AMEC 2003, Melbourne, Australia, July 15. 2003, Revised Selected Papers Redaktion: Faratin, Peyman; Walsh, William E.; Rodríguez-Aguilar, Juan A.; Parkes, David C.
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Autorenporträt
Peyman Faratin, Massachusetts Institute of Technology, Cambridge, USA / David C. Parkes, Havard University, Cambridge, MA, USA / Juan A. Rodríguez-Aguilar, Campus de la Universtitat Autònoma de Barcelona, Spain / William E. Walsh, IBM, T.J.Watson Research Center, New York, NY, USA
Inhaltsangabe
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.
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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