Adaptive negotiation agents for e-business

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

14 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
Pages271-278
Volume113
Publication statusPublished - 2005

Publication series

Name
Volume113

Conference

Title7th International Conference on Electronic Commerce, ICEC05
PlaceChina
CityXi'an
Period15 - 17 August 2005

Abstract

Negotiation has been identified as one of the key steps in Business-to-Business (B2B) transaction models. However, developing effective and efficient negotiation mechanisms for e-Business is quite challenging since negotiations in such a context are characterized by combinatorial complex negotiation spaces, tough deadlines, incomplete information about the opponents, and volatile negotiator preferences. Classical negotiation models are not able to offer a satisfactory solution to address all these issues. This paper illustrates our adaptive negotiation agents which are underpinned by a robust evolutionary learning mechanism to deal with complex and dynamic negotiation situations often encountered in e-Business applications. Our experimental results show that the proposed evolutionary negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for e-Business. Copyright 2005 ACM.

Research Area(s)

  • automated negotiation, e-business, evolutionary learning, intelligent agents

Citation Format(s)

Adaptive negotiation agents for e-business. / Lau, Raymond Y.K.
ACM International Conference Proceeding Series. Vol. 113 2005. p. 271-278.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review