Negotiation Model Based on Artificial Intelligence in the E-Commerce

Shaobin Dong, Aihua Li
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引用次数: 4

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.
基于人工智能的电子商务谈判模型
电子谈判正成为电子商务领域的一个重要研究课题。决策分析尤其是多属性效用理论对电子谈判的支持具有重要作用。首选项通常表示为备选项集上的效用函数,这样用户就会在具有更高效用时更喜欢备选项。人类传统谈判的成功经验是自动谈判的宝贵学习资源。自动谈判模型可以从过去的谈判经验中学习、推理,并给出一个合理的谈判策略选择。人工神经网络和CBR是人工智能中广泛使用相似性的两种方法。基于案例的推理和神经网络在两者之间有着天然的联系。为此,提出了基于神经网络和案例推理的谈判模型。它可以使谈判取得非常好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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