• DocumentCode
    2119355
  • Title

    Negotiation Model Based on Artificial Intelligence in the E-Commerce

  • Author

    Dong, Shaobin ; Li, Aihua

  • Author_Institution
    Huiyin Inst. of Technol., Huaian, China
  • fYear
    2010
  • fDate
    24-26 Dec. 2010
  • Firstpage
    193
  • Lastpage
    196
  • Abstract
    Electronic negotiations are becoming an important research subject in the area of electronic commerce. Decision analysis and especially multiattributive utility theory play an important role for the support of electronic negotiations. The preferences are usually represented as a utility function on the set of alternatives such that the user prefers an alternative exactly when it has higher utility. Successful experience of the human traditional negotiation is the valuable learning resources of automatic negotiation. Automated negotiation model can learn from past experience in negotiation, reason, and give a reasonable choice of negotiations on a new strategy. The ANN and the CBR are two approaches of Artificial Intelligence that use similarity in an extensive way. Case-based reasoning and neural network have a natural link between the two. So it is put forward model of the negotiations based on neural network and case-based reasoning. It can lead that negotiation can be achieved very good results.
  • Keywords
    case-based reasoning; electronic commerce; neural nets; utility theory; ANN; CBR; artificial intelligence; case-based reasoning; decision analysis; e-commerce; electronic commerce; electronic negotiation model; multiattributive utility theory; neural network; Artificial intelligence; Artificial neural networks; Cognition; Consumer electronics; Electronic commerce; Humans; Proposals; ANN; CBR; MAUT; Negotiation Model; Preference elicitation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ISISE), 2010 International Symposium on
  • Conference_Location
    Shanghai
  • ISSN
    2160-1283
  • Print_ISBN
    978-1-61284-428-2
  • Type

    conf

  • DOI
    10.1109/ISISE.2010.41
  • Filename
    5945083