Agent多议题案例协商

Xiangrong Tong, Wei Zhang
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引用次数: 2

摘要

卖方代理通常具有更多的领域知识和经验,这有助于他们获得更好的谈判结果。这激励我们使用基于案例的方法来研究谈判,以便记住以前的案例,并在新的报价中重用该情况的信息和知识。此外,该方法还可以克服agent多议题协商研究的两个不足。一是缺乏对代理经验的使用。二是缺乏代理最优报价策略。为此,提出了一种基于案例的智能体多问题协商模型。本文的重点是基于案例和博弈论的最优报价生成。提出了一种新的相似度评估方法,并详细介绍了失败的案例。原型系统的仿真验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agent Multi-issue Negotiation with Cases
Seller agents usually have more domain knowledge and more experiences which would help them get better negotiation result. This inspires us to investigate negotiation using case-based method in order to remember previous cases and reuse information and knowledge of that situation for new offers. Moreover, it can overcome two shortcomings in agent multi-issue negotiation researches. One is that there is a lack of the use of agent experiences. The other is that there is a lack of agent optimal offer strategy. To this end, a case-based agent multi-issue negotiation model is proposed. The emphasis of the paper is optimal offer generation based on cases and game theory. The novel similarity assessment method is proposed and failed cases are particularly mentioned. Simulation of prototype system demonstrates the effectiveness of the method.
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