Operations Research and Management Science ›› 2014, Vol. 23 ›› Issue (2): 133-138.

• Theory Analysis and Methodology Study • Previous Articles     Next Articles

Research on Emotional Decision Model of Multi-Agent Negotiation

DONG Xue-jie1, JIANG Guo-rui1, HUANG Ti-yun1,2   

  1. 1. School of Economics and Management, Beijing University of Technology, Beijing 100124, China;
    2. School of Management, Harbin Institute of Technology, Harbin 150001, China
  • Received:2012-10-25 Online:2014-02-25

多Agent自动谈判情感决策模型研究

董学杰1, 蒋国瑞1, 黄梯云1,2   

  1. 1.北京工业大学 经济与管理学院,北京 100124;
    2.哈尔滨工业大学 管理学院,黑龙江 哈尔滨 150001
  • 作者简介:董学杰(1975-),男,博士生,主要研究方向为管理信息系统、多Agent自动谈判;蒋国瑞(1954-),男,教授,主要研究方向:管理信息系统、商务智能;黄梯云(1931-),男,教授,博士生导师,主要研究方向为管理信息系统、决策支持系统。
  • 基金资助:
    国家自然科学基金资助项目(71071005)

Abstract: During the negotiation process of automated negotiation based on intelligent agent, the anegotiation agent usully adopts a fixed negotiation strategy, which limited its adaptability in the complex negotiation environment. Based on achievement of emotion theory research, we point out an emotional decision model to improve the degree of intelligence and adaptability of the agent. First, we analyse the emotional decision process of the agent in an automated negotiation, then propose an emotional generation model and emotional decision model in general. Taking single attribute negotiation as an example, we establish a concrete emotional decision model of the negotiation agent. In comparison with non-emotional model, it shows that our emotional decision model can get better result. The results of this research can be applied to various forms of automatic negotiation based on multi-agent.

Key words: management information system, automated negotiation, emotional model, decision model

摘要: 在基于多Agent的自动谈判中,谈判Agent往往采取一个相对固定的策略,使得Agent对动态变化的谈判环境缺乏适应性。根据情感理论的研究成果,本文提出建立情感决策模型来提高Agent的智能程度和适应性。在对谈判Agent情感决策过程进行分析后,建立了一般情况下的情感产生模型和决策模型,并通过在单属性自动谈判环境下,运用具体的情感决策模型和实际数据进行试验,实证了数据模型的有效性。本文的研究成果,可以应用到各种形式的基于多Agent的自动谈判中。

关键词: 管理信息系统, 自动谈判, 情感模型, 决策模型

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