E-Commerce in the Indian Insurance Industry: Prospects and Future
Electronic Commerce Research
Pricing Agents for a Group Buying System
EurAsia-ICT '02 Proceedings of the First EurAsian Conference on Information and Communication Technology
Multi-Attribute Dynamic Pricing for Online Markets Using Intelligent Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Efficient bid pricing based on costing methods for internet bid systems
WISE'06 Proceedings of the 7th international conference on Web Information Systems
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We study the price dynamics in a multi-agent economy consisting of buyers and competing sellers, where each seller has limited information about its competitors' prices. In this economy, buyers use shopbots while the sellers employ automated pricing agents or pricebots. Derivative following (DF) provides a simple, albeit naive, strategy for dynamic pricing in such a scenario. In this work, we refine the DF algorithm and introduce a model optimizer (MO) algorithm that re-estimates the price-profit relationship for a seller at every interval more efficiently. Simulations using the MO pricebots indicate that it outperforms DF even though it has no additional information about the market.