Adaptive Bidding in Single-Sided Auctions Under Uncertainly

by Van Dinther, Clemens

• ISBN13: 9783764380946
• ISBN10: 3764380942
• Format: Paperback
• Copyright: 2007-01-03
• Publisher: Birkhauser

Summary

In the last years electronic markets, especially online auctions, have become very popular and received more and more attention in both, business (B2B) as well as in public practice (B2C and C2C). Science, however, is still far from having studied all phenomena and effects which can be observed on electronic markets. Apart from theoretic analysis, other approaches are necessary to evaluate and understand market effects. This book shows that and how software agents can be used to simulate bidding behaviour in electronic auctions. The main emphasis of this book is to apply computational economics to market theory. It summarizes the most common and up-to-date agent-based simulation methods and tools and develops the simulation software AMASE. On basis of the introduced methods a model is established to simulate bidding behaviour under uncertainty. The book addresses researchers, computer scientists, economists and students who are interested in applying agent-based computational methods to electronic markets. It helps to learn more about simulations in economics in general and common agent-based methods and tools in particular. The reader finds basic definitions and learns how to build an appropriate model for the posed research question. It is the first time that quantitative results are presented for the problem of valuation uncertainty. These results significantly contribute to existing research in computational economics and supplements interesting research aspects.

Table of Contents

List of Figures	p. xiv
List of Tables	p. xviii
Motivation and Fundamentals	p. 1
Introduction	p. 3
Problem Description and Research Questions	p. 5
Organization of the Book	p. 7
Economic Foundations	p. 11
Electronic Markets and Strategic Bidding	p. 11
Historical Background of Markets	p. 12
Markets as an Economic System	p. 13
Market Institution Types and Auctions	p. 18
Bidding in Auctions under Uncertainty	p. 25
Market Engineering	p. 30
Structured Design Approach	p. 31
Generic Design Approaches	p. 35
Computer Aided Market Engineering	p. 38
Conceptual Platform Design	p. 40
The meet2trade Software Suite	p. 42
Summary	p. 45
Agent-based Computational Economics	p. 47
Intelligent Software Agents	p. 50
Characteristics of Software Agents	p. 51
Agent Learning	p. 55
Agent Architecture	p. 56
Multi Agent Systems	p. 57
Communication and Interaction in Multi-Agent Systems	p. 58
Coordination in Multi Agent Systems	p. 60
Building Multi Agent-based Simulation Models	p. 62
Characteristics of Simulations	p. 63
Developing and Applying Simulations	p. 64
Summary	p. 68
Agent-based Simulation Approaches and Tools	p. 69
Methodological Approaches of MABS in Economics	p. 71
Pure Agent-based Simulation: The Bottom-up Approach	p. 73
Monte Carlo Simulation	p. 74
Evolutionary Approach	p. 76
Reinforcement Learning	p. 77
The Learning Model	p. 78
Markov Games	p. 81
Summary	p. 82
Agent-based Simulation Software	p. 85
Design Objectives for Agent-based Simulation Software	p. 86
Functional and Technical Requirements	p. 87
Agent-based Simulation Software - An Overview	p. 91
Requirements Analysis of Agent Platforms	p. 102
The Java Agent Development Framework	p. 106
Agent Platform Architecture	p. 107
Agent Model	p. 108
Development Tools	p. 109
The Agent-based Market Simulation Environment	p. 110
Architecture	p. 110
Simulation Control Agent (SCA)	p. 112
Simulation Agents and Behaviours	p. 117
Examples for Simulations on AMASE	p. 120
Summary	p. 121
Examination of Bidding under Uncertainty	p. 123
Simulation Design	p. 125
The Simulation Model	p. 127
Bidding Process and Action Space	p. 130
Agents and Environment	p. 131
The Reinforcement Learning Mechanism	p. 134
Simulation Approach	p. 136
Initial Parameter Values of the Simulation	p. 136
Simulation Settings	p. 138
Theoretical Benchmark	p. 140
Assessment of the Simulation Results	p. 145
Institutional Rules: Sealed Bid versus Ascending Second Price Auction	p. 147
Two Agent Environment	p. 147
Five Agent Environment	p. 159
Impact of Information Acquisition Cost	p. 165
Two Agent Environment	p. 166
Five Agent Environment	p. 173
Summary	p. 184
Concluding Discussion and Future Research	p. 187
Conclusion	p. 189
Summary of the Main Contributions	p. 189
Limitations of the Approach	p. 192
Outlook	p. 193
Appendices and Bibliography	p. 195
Appendix: Mathematical Proofs	p. 197
Expected Social Welfare	p. 197
Auctioneer's Expected Revenue	p. 198
Bidders' Expected Payoff	p. 199
Uncertain Bidders' Expected Payoff	p. 200
Density Function for the Estimated Valuations	p. 202
Appendix: Simulation Data and Figures	p. 203
Data	p. 203
Institutional Rules: Two Bidder	p. 203
Institutional Rules: Five Bidder	p. 206
Information Acquisition Costs: Two Bidder	p. 207
Information Acquisition Cost: Five Bidder	p. 211
Figures	p. 216
Bibliography	p. 219
Abbreviations	p. 235
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