Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Online learning about other agents in a dynamic multiagent system
AGENTS '98 Proceedings of the second international conference on Autonomous agents
The Michigan Internet AuctionBot: a configurable auction server for human and software agents
AGENTS '98 Proceedings of the second international conference on Autonomous agents
iBundle: an efficient ascending price bundle auction
Proceedings of the 1st ACM conference on Electronic commerce
Decision Support Systems - From information retrieval to knowledge management: enabling technologies and best practices
Efficient mechanisms for the supply of services in multi-agent environments
Decision Support Systems - Special issue on information and computational economics
Proceedings of the fifth international conference on Autonomous agents
Decision Support Systems - Special issue: Formal modeling and electronic commerce
Formal aspects of a generic model of trust for electronic commerce
Decision Support Systems - Special issue: Formal modeling and electronic commerce
Computers play the beer game: can artificial agents manage supply chains?
Decision Support Systems - Special issue: Formal modeling and electronic commerce
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Iterative Combinatorial Auctions: Theory and Practice
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A Multi-Agent Based Negotiation Support System for Distributed Transmission Cost Allocation
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 1 - Volume 1
Multi-Agent Bidding and Contracting for Non-Storable Goods
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 1 - Volume 1
The Emergence of Trust in Multi-Agent Bidding: A Computational Approach
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 1 - Volume 1
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Artificial Agents for Discovering Business Strategies for Network Industries
International Journal of Electronic Commerce
Equilibrium analysis of the possibilities of unenforced exchange in multiagent systems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
The segment approach time axis algorithm for proxy bidding application in online auction
MMACTEE'08 Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering
Behavior-based reputation management in P2P file-sharing networks
Journal of Computer and System Sciences
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A fundamental problem in business-to-business exchanges is the efficient design of mechanisms to promote cooperation and coordination of various self-interested agents. We study the behavior of artificial agents in a bidding and contracting framework [Eur. J. Oper. Res. (2002); D.J. Wu, P. Kleindorfer, J.E. Zhang, Integrating Contracting and Spot Procurement with Capacity Options, Working Paper, Department of Operations and Information Management, The Wharton School, University of Pennsylvania, 2001]. In this framework, there is a long-term contract market as well as a backstop spot market. Seller agents bid their contract offers in terms of price and capacity via an electronic bulletin board, while Buyer agents decide how much to contract with Sellers and how much to shop from the spot market. This two-tiered market has been modeled [Eur. J. Oper. Res. (2002); D.J. Wu, P. Kleindorfer, J.E. Zhang, Integrating Contracting and Spot Procurement with Capacity Options, Working Paper, Department of Operations and Information Management, The Wharton School, University of Pennsylvania, 2001] as a von-Stackelberg game with Seller agents as leaders, and the necessary and sufficient conditions for the existence of market equilibrium are given. What happens if the resulting equilibrium is noncooperative and Pareto dominated by some nonequilibrium bidding? What happens if there are multiple equilibria, some Pareto dominated by others, then which will be selected? What happens when there is no equilibrium? The goal of this paper is to study equilibrium and disequilibrium behavior of artificial agents in such systems, and explore the efficient design of mechanisms to promote cooperation and coordination of self-interested artificial agents.