An evolutionary approach for intelligent negotiation agents in e-marketplaces

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 12 - Chapter in an edited book (Author)peer-review

7 Citations (Scopus)

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. © 2009 Springer-Verlag Berlin Heidelberg.
Original languageEnglish
Title of host publicationIntelligent Agents in the Evolution of Web and Applications
PublisherSpringer 
Pages279-301
ISBN (Print)9783540880707
DOIs
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence
Volume167
ISSN (Print)1860-949X

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