Abstract
The problem of how to design personal, intelligent agents for e-commerce applications is a subject of increasing interest from both the academic and industrial research communities. In our research, we consider the agent environment as an open marketplace which is populated with economic agents (buyers and sellers), freely entering or leaving the market. The problem we are addressing is how best to model the electronic marketplace, and what kinds of learning strategies should be provided, in order to improve the performance of both buyers and sellers in electronic exchanges.
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R. G. Smith. The Contract Net Protocol: High Level Communication and Control in a Distributed Problem Solver. In IEEE Transactions on Computers, C-29(12): 1104–1113, December 1980.
J. M. Vidal, and E. H. Durfee. The Impact of Nested Agent Models in an Information Economy. In Proceedings of the Second International Conference on Multi-Agent Systems, pages 377–384, 1996.
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© 2002 Springer-Verlag Berlin Heidelberg
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Tran, T., Cohen, R. (2002). A Learning Algorithm for Buying and Selling Agents in Electronic Marketplaces. In: Cohen, R., Spencer, B. (eds) Advances in Artificial Intelligence. Canadian AI 2002. Lecture Notes in Computer Science(), vol 2338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47922-8_38
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DOI: https://doi.org/10.1007/3-540-47922-8_38
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