InfoSleuth: agent-based semantic integration of information in open and dynamic environments
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Design and implementation of an agent-based intermediary infrastructure for electronic markets
Proceedings of the 2nd ACM conference on Electronic commerce
An experimental analysis of multi-attribute auctions
Decision Support Systems
Protocols and strategies for automated multi-attribute auctions
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Modern Information Retrieval
Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace
Autonomous Agents and Multi-Agent Systems
Agent-Mediated Integrative Negotiation for Retail Electronic Commerce
AMET '98 Selected Papers from the First International Workshop on Agent Mediated Electronic Trading on Agent Mediated Electronic Commerce
On Agent-Mediated Electronic Commerce
IEEE Transactions on Knowledge and Data Engineering
B2b Integration: A Practical Guide to Collaborative E-Commerce
B2b Integration: A Practical Guide to Collaborative E-Commerce
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Perspectives of agent technology in E-procurement
AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6
A behaviour network approach to support opportunity-based virtual enterprises in the internet
Multiagent and Grid Systems
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This paper proposes a new e-procurement model for a large number of buyers and sellers interacting via the Internet. The goal of e-procurement is to create a satisfactory match between buyers’ demand and sellers’ supply. From our real-world experience, we view e-procurement as a process of negotiation to increase the matching quality of two corresponding specifications: one for buyers’ demand and another for sellers’ supply. To model scalable e-procurement, we propose a co-adaptive matchmaking mechanism using mutual relevance feedback. In order to understand the nature of the mechanism, we have developed two types of software agents, called e-buyers and e-sellers, to simulate human buyers and sellers. Multiagent simulation results show that the matching quality is incrementally improved if agents adaptively change their specifications. A realistic example is also provided to discuss how to extend our simulation to real-world e-procurement infrastructure.