C4.5: programs for machine learning
C4.5: programs for machine learning
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Proceedings of the 1st ACM conference on Electronic commerce
Learning Curve: A Simulation-Based Approach to Dynamic Pricing
Electronic Commerce Research
A Simulation-Based Approach for Testing Market Strategies in Electronic MarketPlaces
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Agent-based simulation of electronic marketplaces with decision support
Proceedings of the 2008 ACM symposium on Applied computing
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We forecast a future in which the global economy and the Internet will host a large number of interacting software agents. Most of them will be economically motivated, and will negotiate a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use all available means to anticipate their collective interactions. This paper addresses this concern by presenting a multi-agent market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms. The results of the negotiations between agents will be analysed by data mining tools in order to extract rules that will give the agents feedback to improve their strategies.