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Intelligent Agents in the Evolution of Web and Applications pp 279–301Cite as

An Evolutionary Approach for Intelligent Negotiation Agents in e-Marketplaces

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 167))

Abstract

Automated negotiation mechanisms are desirable to enhance the throughput of e-marketplaces. However, existing negotiation mechanisms are weak in supporting real-world negotiations because they assume the availability of complete information about static negotiation spaces where both negotiator’s preferences and market conditions remain unchanged. This article illustrates the design and development of evolutionary negotiation agents which are able to learn from and adapt to dynamic negotiation environment. Our experimental results show that the proposed evolutionary negotiation agents outperform a Pareto optimal negotiation mechanism under dynamic negotiation conditions such as the presence of time pressure. These agents can also achieve near optimal negotiation outcomes under dynamic negotiation environment. Our research work opens the door to the development of intelligent negotiation agents to streamline real-world e-marketplaces.

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Author information

Authors and Affiliations

  1. Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR,  

    Raymond Y. K. Lau

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  1. Raymond Y. K. Lau
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Editors and Affiliations

  1. Wroclaw University of Technolgy, Poland

    Ngoc Thanh Nguyen

  2. University of South Australia, Australia

    Lakhmi C. Jain

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Lau, R.Y.K. (2009). An Evolutionary Approach for Intelligent Negotiation Agents in e-Marketplaces. In: Nguyen, N.T., Jain, L.C. (eds) Intelligent Agents in the Evolution of Web and Applications. Studies in Computational Intelligence, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88071-4_12

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  • DOI: https://doi.org/10.1007/978-3-540-88071-4_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88070-7

  • Online ISBN: 978-3-540-88071-4

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