Agent-Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems, AAMAS 2004 Workshop, Amec 2004, New York, v. 6

This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Agent-Mediated Electronic Commerce, AMEC 2006, held in New York, NY, USA in July 2004 as part of AAMAS 2004. The 15 revised full papers presented were carefully selected from 39 submissions during two rounds of reviewing and revision. The papers bring together novel work from such diverse fields as Computer Science, Operations Research, Artificial Intelligence and Distributed Systems that focus on modeling, implementation and evaluation of computational trading institution and/or agent strategies over a diverse set of goods. They are organized in topical sections on mechanism design, trading agents, and tools. Front matter......Page 1 Introduction......Page 10 The VCG Mechanism......Page 12 Characterization......Page 13 Review......Page 14 Characterization......Page 15 Complexity......Page 16 Motivating Example......Page 17 Characterization......Page 18 Complexity......Page 19 Review......Page 20 Conclusion......Page 21 Future Research......Page 22 Introduction......Page 24 Related Work......Page 26 The Multiple Good Interdependent Mechanism......Page 27 Example of an Interdependent Valuation Scenario......Page 29 Properties of the Mechanism......Page 32 Economic Properties......Page 33 Computational Properties......Page 35 Conclusions and Future Work......Page 36 Social Choice Problems......Page 39 Modeling Social Choice Problems......Page 41 Budget Balanced Mechanisms for Social Choice......Page 43 Examples and Experimental Results......Page 46 Collusion......Page 49 Related Work......Page 50 Conclusions......Page 51 Introduction......Page 53 The Composability Problem......Page 55 The Model......Page 56 Auctions for Options......Page 58 Truthful Bidding to Proxy Agent......Page 60 Experiments......Page 61 Conclusion......Page 65 Introduction......Page 68 Truthful Feedback......Page 70 Limits of Feasibility......Page 71 The ``CONFESS'' Mechanism......Page 73 Equilibrium Analysis......Page 74 Open Issues......Page 79 Conclusions......Page 80 Introduction......Page 82 Motivation: Data Center Allocation......Page 83 Problem Formulation......Page 85 Auction and KP Taxonomies......Page 86 Dynamic Programming Solver......Page 87 Computational Complexity......Page 88 Hard Knapsack Problems......Page 89 WDP-KP Connections......Page 90 Multi-unit Auction WDPs......Page 91 Discussion......Page 92 Introduction......Page 96 An Example Application......Page 97 Mechanism Design for Rational Agents......Page 98 Computationally-Limited Agents......Page 99 A Model of a Computationally-Limited Agent......Page 100 Strategic Behavior of Deliberative Agents......Page 101 A Revelation Principle......Page 103 Properties of the Auctions......Page 104 Results......Page 105 Related Research......Page 107 Conclusions and Future Research......Page 108 Introduction......Page 110 The Continuous Double Auction Verses the Clearing-House......Page 113 Basic Approach......Page 114 Experimental Setup......Page 115 Dynamic Analysis......Page 116 Results......Page 117 Discussion......Page 120 Further Work......Page 121 Introduction......Page 124 Bidding Agent......Page 125 Agent Architecture......Page 126 Maximum Entropy Inference......Page 127 Representation Dependence......Page 128 From Utility to Acceptability......Page 129 Auctions......Page 133 Take-it-or-Leave-it......Page 135 Conclusions......Page 136 Introduction......Page 138 Time Pressure......Page 140 One-to-Many Bargaining Strategies......Page 141 The Bargaining Game......Page 143 Buyers and Their Agents......Page 144 The Evolutionary Algorithm......Page 145 Settings......Page 146 Results......Page 147 Bargaining Revisited......Page 149 Concluding Remarks......Page 150 Introduction......Page 152 The TAC SCM Game......Page 153 Problem Specification......Page 154 Learning Auction-Winning Probabilities......Page 155 Algorithm Comparison......Page 156 Choice of Training Data......Page 157 Problem Formulation......Page 159 Optimization Method......Page 160 Agent Design......Page 163 Results......Page 164 Future Work and Conclusion......Page 165 Introduction......Page 167 Related Work......Page 170 The Dual Parallel Two-Sided Search Model......Page 171 Agents Strategies and Equilibrium Dynamics......Page 172 Reservation Value and Expected Utility Function......Page 173 Dual Parallel Two-Sided Search Strategy......Page 174 Finding the Equilibrium......Page 176 The Incentive to Use Parallel Search......Page 177 Conclusions......Page 179 Introduction......Page 182 Background......Page 183 Related Work......Page 184 Approach and Assumptions......Page 185 Strategy Design......Page 186 Parameter Choices......Page 187 The Trend-Following Agent......Page 188 The Market-Making Agent......Page 190 Reinforcement Learning......Page 191 Trend Following......Page 192 Comparative Analysis......Page 193 Live Competition Results......Page 194 Conclusions and Future Work......Page 195 Introduction......Page 197 Related Work......Page 198 Framework Overview......Page 199 eBay Example......Page 200 Rights and Obligations......Page 201 Objects, States, Actions......Page 203 Ownership and Possession......Page 204 Example Representations......Page 206 Open-Cry English Auction......Page 207 Sealed-Bid Second-Price Auction......Page 208 Conclusions......Page 209 Introduction......Page 211 Problem Definition......Page 213 MAUT-Based Bundle Evaluation......Page 214 Optimisation Algorithm......Page 216 Implementation......Page 217 Results......Page 218 Case Study: Electricity Purchase......Page 219 Case Study: Transportation Purchase......Page 220 References......Page 222 Back matter......Page 224 '6th Workshop on Agent-Mediated Electronic Commerce (AMEC VI) held in conjunction with the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS)'--Pref.