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
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Learning Curve: A Simulation-Based Approach to Dynamic Pricing
Electronic Commerce Research
An agenda-based framework for multi-issue negotiation
Artificial Intelligence
Simulating the Behaviour of Electronic MarketPlaces with an Agent-Based Approach
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Mascem: A Multiagent System That Simulates Competitive Electricity Markets
IEEE Intelligent Systems
ISEM: a multiagent Simulator for testing agent market strategies
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.