Agent-mediated electronic commerce: automated negotiation and strategy design for electronic markets. AAMAS 2006 workshop, Tada/Amec 2006, Hakodate, Japan, May 9, 2006, selected and revised papers

Maria Fasli, Onn Shehory3540725016, 9783540725015, 9783540725022

This book constitutes the thoroughly refereed post-proceedings of the joint International Workshops on Trading Agent Design and Analysis, TADA 2006, and on Agent Mediated Electronic Commerce, AMEC VIII 2006, held in Hakodate, Japan, in May 2006 as an associated event of AAMAS 2006, the 5th International Joint Conference on Autonomous Agents and Multiagent Systems.

The 17 revised full papers presented were carefully selected from the presentations made at the workshop and include papers from the annual TAC tournament whose purpose is to stimulate research in trading agents and market mechanisms by providing a platform for agents competing in well-defined market scenarios. The papers address a mix of both theoretical and practical issues in trading agent design and technologies, theoretical and empirical evaluation of strategies in complex trading scenarios as well as mechanism design. Also covered are issues of agent-mediated electronic commerce ranging from the design of electronic marketplaces and efficient protocols to behavioral aspects of agents operating in such environments.

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Table of contents :
Front Matter……Page 1
ISBN
……Page 3
Preface……Page 4
Table of Contents……Page 6
Introduction……Page 8
The Original Eight-Parameter ZIP……Page 10
Previous ZIP8 Results……Page 12
From 8 to 60 in Five Paragraphs……Page 14
ZIP60 Results: Control of Search-Space Dimensionality Required……Page 16
Principal Component Analysis……Page 19
Conclusions……Page 20
References……Page 21
Introduction……Page 24
Background……Page 26
Transformability Network Structures……Page 27
WDP for MUCRA with t-Relationships……Page 28
Mapping to Integer Programming……Page 29
Data Set Generation……Page 30
Experimental Settings and Results……Page 35
Conclusions and Future Work……Page 37
Introduction……Page 38
Single-Issue Negotiation……Page 39
Multi-issue Negotiation with Complete Information……Page 40
Multi-issue Negotiation with Uncertainty About Deadlines……Page 45
Related Work……Page 50
Conclusions and Future Work……Page 51
Introduction……Page 53
Computer Sales……Page 54
Overview of TacTex-05……Page 55
Offer Acceptance Predictor……Page 56
Demand Manager……Page 57
Supply Manager……Page 58
Adaptation over a Series of Games……Page 59
Initial Component Orders……Page 60
Endgame Sales……Page 61
Competition Results and Additional Experiments……Page 62
Initial Component Orders During the Competition……Page 63
Experimenting with Initial Component Orders……Page 64
Endgame Sales During the Competition……Page 65
Related Work……Page 66
Conclusion……Page 67
Introduction……Page 69
Calculating Market Efficiency……Page 70
0-1 Multiple Knapsack Solver……Page 72
Market Efficiency Comparison……Page 73
Market Share……Page 74
Average Sales Price……Page 75
Bid Efficiency……Page 76
Bullwhip Effect……Page 77
Conclusion……Page 80
Introduction……Page 82
Iterative RFP Coalition Formation Method……Page 83
Problem Definition and Agent Based Models……Page 84
Conservative and Competitive Strategies……Page 86
Theoretical Dynamics of Pure Conservative Population……Page 87
Experimental Set-Up……Page 89
Conservative Behavior Experiments……Page 90
Mixed Strategies Dynamics Experiments……Page 92
Related Work……Page 93
Conclusions……Page 94
Ongoing and Future Work……Page 95
Introduction……Page 97
Game Overview……Page 99
Summary of Daily Activities……Page 100
House Attributes, Listings……Page 101
Transaction Attributes……Page 102
Utility Functions……Page 103
Preference Elicitation……Page 104
Negotiating……Page 105
Obtaining/Losing Clients……Page 106
Duration……Page 107
Final Remarks……Page 108
Introduction……Page 110
Modelling the Behavioural Types……Page 112
An Evolutionary Game-Theoretic Model……Page 115
Computing the Heuristic Payoff Table……Page 116
Computing the Equilibrium……Page 117
An Empirical Analysis of the Behavioural Types……Page 118
Static Environments……Page 119
Dynamic Environments……Page 120
Conclusions and Future Work……Page 122
Introduction……Page 125
Interaction Shop and Customer……Page 126
Advising Mechanism……Page 128
Customer Preferences……Page 129
Learning Problem……Page 130
Learning Method……Page 131
Estimating Mean and Covariance Matrix……Page 132
Preprocessing Negotiation Data……Page 133
Experimental Design……Page 134
Results……Page 135
Conclusions……Page 137
Introduction……Page 139
Related Work on Pricing Problems……Page 140
Related Work on Learning Valuations……Page 141
P3ID……Page 142
P3ID and CKP Equivalence……Page 143
Example Problem……Page 144
Characterizing an Optimal Solution……Page 145
Finding $delta$*……Page 147
Shared Resource Extension……Page 148
Normal Distribution Trees……Page 149
Learning Customer Valuations in TAC……Page 150
Empirical Setup……Page 151
Empirical Results……Page 152
Conclusion……Page 154
Introduction……Page 156
Combinatorial Auctions in Grid Environments……Page 157
An Agent-Based Simulation Environment for Combinatorial Resource Allocation in Grid Systems……Page 158
Scenario for a PCRA in a Combinatorial Grid System……Page 159
The Combinatorial Scheduling Auction……Page 160
The Combinatorial Auctioneer……Page 162
The Task Agents’ Bidding Model……Page 164
Testing Bidding Strategies……Page 165
Conclusion……Page 169
Introduction……Page 171
The Auction Setting……Page 172
Single Object……Page 174
Multiple Sequential Auctions……Page 175
Multiple Simultaneous Auctions……Page 179
A Comparison of the Two Auction Mechanisms……Page 180
Related Work……Page 182
Conclusions and Future Work……Page 183
Introduction……Page 185
Related Work……Page 186
Reducing Variability of the Gamespace……Page 187
Controlling the Market Conditions……Page 188
Experiments……Page 190
Conclusion……Page 193
Future Work……Page 194
Introduction……Page 196
The Mediator……Page 198
Analysis……Page 199
Seller Equilibrium Behaviour……Page 200
Auction Fees and Market Efficiency……Page 203
Evolutionary Simulation……Page 204
Evolutionary vs. Analytical Results……Page 205
Efficiency……Page 206
Auction Fees……Page 207
Related Work……Page 208
Conclusions……Page 209
Introduction……Page 211
The Setting……Page 213
Optimal Incentive Compatible Feedback Payments……Page 214
Honest Reporting with Unknown Beliefs……Page 216
Declaration of Private Information……Page 217
Robust Incentive Compatible Payments……Page 218
General Tolerance Intervals for Private Information……Page 220
Discussion……Page 222
Conclusion……Page 223
Generating Random Settings……Page 224
Introduction……Page 226
The TAC SCM Game……Page 227
The CrocodileAgent……Page 228
Negotiation of Supply Contracts……Page 229
Bidding for Customer Orders……Page 231
Managing Daily Assembly Activities and Shipping Completed Orders to Customers……Page 233
TAC SCM 2005 Competition……Page 234
Controlled Experiments……Page 235
References……Page 239
Introduction……Page 241
The Fuzzy Constraint Satisfaction Problems (FCSPs) Framework……Page 242
Domain Knowledge of the Buyer Agent……Page 243
A Purchase Negotiation Dialogue……Page 244
The Decision Mechanisms……Page 245
Operational Semantics……Page 249
A Purchase Scenario……Page 250
Conclusions and Future Work……Page 253
18 back-matter……Page 255